Mining DNA methylation alterations towards a classification of placental pathologies

CWGCNA: an R package to perform causal inference from the WGCNA framework

WGCNA (weighted gene co-expression network analysis) is a very useful tool for identifying co-expressed gene modules and detecting their correlations to phenotypic traits. Here, we explored more possibilities about it and developed the R package CWGCNA (causal WGCNA), which works from the traditional WGCNA pipeline but mines more information. It couples a mediation model with WGCNA, so the causal relationships among WGCNA modules, module features, and phenotypes can be found, demonstrating whether the module change causes the phenotype change or vice versa. After that, when annotating the module gene set functions, it uses a novel network-based method, considering the modules' topological structures and capturing their influence on the gene set functions. In addition to conducting these biological explorations, CWGCNA also contains a machine learning section to perform clustering and classification on multi-omics data, given the increasing popularity of this data type. Some basic functions, such as differential feature identification, are also available in our package. Its effectiveness is proved by the performance on three single or multi-omics datasets, showing better performance than existing methods. CWGCNA is available at: https://github.com/yuabrahamliu/CWGCNA.

Development and Validation of a Novel Placental DNA Methylation Biomarker of Maternal Smoking during Pregnancy in the ECHO Program

BACKGROUND

Maternal cigarette smoking during pregnancy (MSDP) is associated with numerous adverse health outcomes in infants and children with potential lifelong consequences. Negative effects of MSDP on placental DNA methylation (DNAm), placental structure, and function are well established.

OBJECTIVE

Our aim was to develop biomarkers of MSDP using DNAm measured in placentas (N = 96 ), collected as part of the Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function double-blind, placebo-controlled randomized clinical trial conducted between 2012 and 2016. We also aimed to develop a digital polymerase chain reaction (PCR) assay for the top ranking cytosine-guanine dinucleotide (CpG) so that large numbers of samples can be screened for exposure at low cost.

METHODS

We compared the ability of four machine learning methods [logistic least absolute shrinkage and selection operator (LASSO) regression, logistic elastic net regression, random forest, and gradient boosting machine] to classify MSDP based on placental DNAm signatures. We developed separate models using the complete EPIC array dataset and on the subset of probes also found on the 450K array so that models exist for both platforms. For comparison, we developed a model using CpGs previously associated with MSDP in placenta. For each final model, we used model coefficients and normalized beta values to calculate placental smoking index (PSI) scores for each sample. Final models were validated in two external datasets: the Extremely Low Gestational Age Newborn observational study, N = 426 ; and the Rhode Island Children's Health Study, N = 237 .

RESULTS

Logistic LASSO regression demonstrated the highest performance in cross-validation testing with the lowest number of input CpGs. Accuracy was greatest in external datasets when using models developed for the same platform. PSI scores in smokers only (n = 72 ) were moderately correlated with maternal plasma cotinine levels. One CpG (cg27402634), with the largest coefficient in two models, was measured accurately by digital PCR compared with measurement by EPIC array (R 2 = 0.98 ).

DISCUSSION

To our knowledge, we have developed the first placental DNAm-based biomarkers of MSDP with broad utility to studies of prenatal disease origins. https://doi.org/10.1289/EHP13838.

Genetic variation and pesticide exposure influence blood DNA methylation signatures in females with early-stage Parkinson's disease

Although sex, genetics, and exposures can individually influence risk for sporadic Parkinson's disease (PD), the joint contributions of these factors to the epigenetic etiology of PD have not been comprehensively assessed. Here, we profiled sex-stratified genome-wide blood DNAm patterns, SNP genotype, and pesticide exposure in agricultural workers (71 early-stage PD cases, 147 controls) and explored replication in three independent samples of varying demographics (n = 218, 222, and 872). Using a region-based approach, we found more associations of blood DNAm with PD in females (69 regions) than in males (2 regions, Δβadj| ≥0.03, padj ≤ 0.05). For 48 regions in females, models including genotype or genotype and pesticide exposure substantially improved in explaining interindividual variation in DNAm (padj ≤ 0.05), and accounting for these variables decreased the estimated effect of PD on DNAm. The results suggested that genotype, and to a lesser degree, genotype-exposure interactions contributed to variation in PD-associated DNAm. Our findings should be further explored in larger study populations and in experimental systems, preferably with precise measures of exposure.

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.

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.

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.

Placental Mitochondrial Function and Dysfunction in Preeclampsia

The placenta is a vital organ of pregnancy, regulating adaptation to pregnancy, gestational parent/fetal exchange, and ultimately, fetal development and growth. Not surprisingly, in cases of placental dysfunction-where aspects of placental development or function become compromised-adverse pregnancy outcomes can result. One common placenta-mediated disorder of pregnancy is preeclampsia (PE), a hypertensive disorder of pregnancy with a highly heterogeneous clinical presentation. The wide array of clinical characteristics observed in pregnant individuals and neonates of a PE pregnancy are likely the result of distinct forms of placental pathology underlying the PE diagnosis, explaining why no one common intervention has proven effective in the prevention or treatment of PE. The historical paradigm of placental pathology in PE highlights an important role for utero-placental malperfusion, placental hypoxia and oxidative stress, and a critical role for placental mitochondrial dysfunction in the pathogenesis and progression of the disease. In the current review, the evidence of placental mitochondrial dysfunction in the context of PE will be summarized, highlighting how altered mitochondrial function may be a common feature across distinct PE subtypes. Further, advances in this field of study and therapeutic targeting of mitochondria as a promising intervention for PE will be discussed.

Targeted bisulfite resequencing of differentially methylated cytosines in pre-eclampsia reveals a skewed dynamic balance in the DNA methylation of enhancers

Pre-eclampsia (PE) is a major hypertensive disorder of pregnancy. Widespread differentially methylated cytosines (DMCs) with modest changes in methylation level are associated with PE, whereas their cause and biological significance remain unknown. We aimed to clarify DNA methylation patterns around DMCs in 103 placentas using MethylCap targeted bisulfite re-sequencing (MethylCap-seq) assays of 690 selected DMCs. We verified the MethylCap-seq method, then validated 677 (98.1%) of DMCs (vDMCs) in an independent cohort. The validated DMCs were strongly enriched in active placenta-specific enhancers and showed highly dynamic methylation levels. We found high epigenetic heterogeneity between vDMCs and adjacent CpG sites (r2 < 0.2) and a significant decrease in PE in the discovery and replication cohorts (P = 2.00 × 10-24 and 6.43 × 10-9, respectively). We replicated the methylation changes in a hypoxia/reoxygenation cell model. We constructed 112 methylation haplotype blocks and found that the frequencies of unmethylated haplotypes (UMHs) were dynamic with gestational age (GA) and were altered in maternal plasma of patients with PE. Our results uncovered additional DNA methylation features in PE placentas and suggested a model of skewed DNA methylation balance of enhancers in PE.

eClock: An ensemble-based method to accurately predict ages with a biased distribution from DNA methylation data

DNA methylation is closely related to senescence, so it has been used to develop statistical models, called clock models, to predict chronological ages accurately. However, because the training data always have a biased age distribution, the model performance becomes weak for the samples with a small age distribution density. To solve this problem, we developed the R package eClock, which uses a bagging-SMOTE method to adjust the biased distribution and predict age with an ensemble model. Moreover, it also provides a bootstrapped model based on bagging only and a traditional clock model. The performance on three datasets showed that the bagging-SMOTE model significantly improved rare sample age prediction. In addition to model construction, the package also provides other functions such as data visualization and methylation feature conversion to facilitate the research in relevant areas.

Gene model-related m6A expression levels predict the risk of preeclampsia

Background

This is the first study to explore the potential functions and expression patterns of RNA N6-methyladenosine (m6A) and potential related genes in preeclampsia.

Methods

We identified two m6A modification patterns through unsupervised cluster analysis and validated them by principal component analysis. We quantified the relative abundance of specific infiltrating immunocytes using single-sample gene set enrichment analysis (ssGSEA) and the Wilcoxon test. To screen hub genes related to m6A regulators, we performed weighted gene coexpression network analysis. Functional enrichment analysis was conducted for differential signalling pathways and cellular processes. Preeclampsia patients were grouped by consensus clustering based on differentially expressed hub genes and the relationship between different gene-mediated classifications and clinical features.

Results

Two m6A clusters in preeclampsia, cluster A and cluster B, were determined based on the expression of 17 m6A modification regulators; ssGSEA revealed seven significantly different immune cell subtypes between the two clusters. A total of 1393 DEGs and nine potential m6A-modified hub genes were screened. We divided the patients into two groups based on the expression of these nine genes. We found that almost all the patients in m6A cluster A were classified into hub gene cluster 1 and that a lower gestational age may be associated with more m6A-associated events.

Conclusions

This study revealed that hub gene-mediated classification is consistent with m6A modification clusters for predicting the clinical characteristics of patients with preeclampsia. Our results provide new insights into the molecular mechanisms of preeclampsia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01254-4.

Epigenetic processes during preeclampsia and effects on fetal development and chronic health

Preeclampsia (PE), the leading cause of maternal and fetal morbidity and mortality, is associated with poor fetal growth, intrauterine growth restriction (IUGR) and low birth weight (LBW). Offspring of women who had PE are at increased risk for cardiovascular (CV) disease later in life. However, the exact etiology of PE is unknown. Moreover, there are no effective interventions to treat PE or alleviate IUGR and the developmental origins of chronic disease in the offspring. The placenta is critical to fetal growth and development. Epigenetic regulatory processes such as histone modifications, microRNAs and DNA methylation play an important role in placental development including contributions to the regulation of trophoblast invasion and remodeling of the spiral arteries. Epigenetic processes that lead to changes in placental gene expression in PE mediate downstream effects that contribute to the development of placenta dysfunction, a critical mediator in the onset of PE, impaired fetal growth and IUGR. Therefore, this review will focus on epigenetic processes that contribute to the pathogenesis of PE and IUGR. Understanding the epigenetic mechanisms that contribute to normal placental development and the initiating events in PE may lead to novel therapeutic targets in PE that improve fetal growth and mitigate increased CV risk in the offspring.

DNA methylation-based sex classifier to predict sex and identify sex chromosome aneuploidy

Background

Sex is an important covariate of epigenome-wide association studies due to its strong influence on DNA methylation patterns across numerous genomic positions. Nevertheless, many samples on the Gene Expression Omnibus (GEO) frequently lack a sex annotation or are incorrectly labelled. Considering the influence that sex imposes on DNA methylation patterns, it is necessary to ensure that methods for filtering poor samples and checking of sex assignment are accurate and widely applicable.

Results

Here we presented a novel method to predict sex using only DNA methylation beta values, which can be readily applied to almost all DNA methylation datasets of different formats (raw IDATs or text files with only signal intensities) uploaded to GEO. We identified 4345 significantly (p<0.01) sex-associated CpG sites present on both 450K and EPIC arrays, and constructed a sex classifier based on the two first principal components of the DNA methylation data of sex-associated probes mapped on sex chromosomes. The proposed method is constructed using whole blood samples and exhibits good performance across a wide range of tissues. We further demonstrated that our method can be used to identify samples with sex chromosome aneuploidy, this function is validated by five Turner syndrome cases and one Klinefelter syndrome case.

Conclusions

This proposed sex classifier not only can be used for sex predictions but also applied to identify samples with sex chromosome aneuploidy, and it is freely and easily accessible by calling the ‘estimateSex’ function from the newest wateRmelon Bioconductor package (https://github.com/schalkwyk/wateRmelon).

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-021-07675-2).

Identification and validation of DNA methylation changes in pre-eclampsia

INTRODUCTION

Pre-eclampsia (PE) is a dangerous placental condition that can lead to premature labour, seizures and death of mother and infant. Several studies have identified altered placental DNA methylation in PE; however, there is widespread inconsistency between studies and most findings have not been replicated. This study aimed to identify and validate consistent differences in methylation across multiple PE cohorts.

METHODS

Seven publicly available 450K methylation array datasets were analysed to identify consistent differentially methylated positions (DMPs) in PE. DMPs were identified based on methylation difference (≥10%) and significance (p-value ≤ 1 × 10^-7). Targeted deep bisulfite sequencing was then performed to validate a subset of DMPs in an additional independent PE cohort.

RESULTS

Stringent analysis of the seven 450K datasets identified 25 DMPs (associated with 11 genes) in only one dataset. Using more relaxed criteria confirmed 19 of the stringent 25 DMPs in at least four of the remaining six datasets. Targeted deep bisulfite sequencing of eight DMPs (associated with three genes; CMIP, ST3GAL1 and DAPK3) in an independent PE cohort validated two DMPs in the CMIP gene. Seven additional CpG sites in CMIP were found to be significantly differentially methylated in PE.

DISCUSSION

The identification and validation of significant differential methylation in CMIP suggests that the altered DNA methylation of this gene may be associated with the pathogenesis of PE, and may have the potential to serve as diagnostic biomarkers for this dangerous condition of pregnancy.

A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta

BACKGROUND

Human placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal DNAme in the uncomplicated term placenta (n = 343) using the Illumina 450K array.

RESULTS

At a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex and replicated in an independent cohort of samples (n = 293). Several of these differentially methylated CpG sites were part of larger correlated regions of sex differential DNAme. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Patterns of autosomal DNAme at these 162 CpGs were significantly associated with maternal age (in males) and newborn birthweight standard deviation (in females).

CONCLUSIONS

Our results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

Subtypes of Preeclampsia: Recognition and Determining Clinical Usefulness

The concept that preeclampsia is a multisystemic syndrome is appreciated in both research and clinical care. Our understanding of pathophysiology recognizes the role of inflammation, oxidative and endoplasm reticulum stress, and angiogenic dysfunction. Yet, we have not progressed greatly toward clinically useful prediction nor had substantial success in prevention or treatment. One possibility is that the maternal syndrome may be reached through different pathophysiological pathways, that is, subtypes of preeclampsia, that in their specificity yield more clinical utility. For example, early and late onset preeclampsia are increasingly acknowledged as different pathophysiological processes leading to a common presentation. Other subtypes of preeclampsia are supported by disparate clinical outcomes, long-range prognosis, organ systems involved, and risk factors. These insights have been supplemented by discovery-driven methods, which cluster preeclampsia cases into groups indicating different pathophysiologies. In this presentation, we review likely subtypes based on current knowledge and suggest others. We present a consideration of the requirements for a clinically meaningful preeclampsia subtype. A useful subtype should (1) identify a specific pathophysiological pathway or (2) specifically indicate maternal or fetal outcome, (3) be recognizable in a clinically useful time frame, and (4) these results should be reproducible and generalizable (but at varying frequency) including in low resource settings. We recommend that the default consideration be that preeclampsia includes several subtypes rather than trying to force all cases into a single pathophysiological pathway. The recognition of subtypes and deciphering their different pathophysiologies will provide specific targets for prevention, prediction, and treatment directing personalized care.

Maternal DNA Methylation During Pregnancy: a Review

Multiple environmental, behavioral, and hereditary factors affect pregnancy. Recent studies suggest that epigenetic modifications, such as DNA methylation (DNAm), affect both maternal and fetal health during the period of gestation. Some of the pregnancy-related risk factors can influence maternal DNAm, thus predisposing both the mother and the neonate to clinical adversities with long-lasting consequences. DNAm alterations in the promoter and enhancer regions modulate gene expression changes which play vital physiological role. In this review, we have discussed the recent advances in our understanding of maternal DNA methylation changes during pregnancy and its associated complications such as gestational diabetes and anemia, adverse pregnancy outcomes like preterm birth, and preeclampsia. We have also highlighted some major gaps and limitations in the area which if addressed might improve our understanding of pregnancy and its associated adverse clinical conditions, ultimately leading to healthy pregnancies and reduction of public health burden.

From Maternal Diet to Neurodevelopmental Disorders: A Story of Neuroinflammation

Providing the appropriate quantity and quality of food needed for both the mother's well-being and the healthy development of the offspring is crucial during pregnancy. However, the macro- and micronutrient intake also impacts the body's regulatory supersystems of the mother, such as the immune, endocrine, and nervous systems, which ultimately influence the overall development of the offspring. Of particular importance is the association between unhealthy maternal diet and neurodevelopmental disorders in the offspring. Epidemiological studies have linked neurodevelopmental disorders like autism spectrum disorders, attention-deficit-hyperactivity disorder, and schizophrenia, to maternal immune activation (MIA) during gestation. While the deleterious consequences of diet-induced MIA on offspring neurodevelopment are increasingly revealed, neuroinflammation is emerging as a key underlying mechanism. In this review, we compile the evidence available on how the mother and offspring are both impacted by maternal dietary imbalance. We specifically explore the various inflammatory and anti-inflammatory effects of dietary components and discuss how changes in inflammatory status can prime the offspring brain development toward neurodevelopmental disorders. Lastly, we discuss research evidence on the mechanisms that sustain the relationship between maternal dietary imbalance and offspring brain development, involving altered neuroinflammatory status in the offspring, as well as genetic to cellular programming notably of microglia, and the evidence that the gut microbiome may act as a key mediator.

Genomic imbalances in the placenta are associated with poor fetal growth

Background

Fetal growth restriction (FGR) is associated with increased risks for complications before, during, and after birth, in addition to risk of disease through to adulthood. Although placental insufficiency, failure to supply the fetus with adequate nutrients, underlies most cases of FGR, its causes are diverse and not fully understood. One of the few diagnosable causes of placental insufficiency in ongoing pregnancies is the presence of large chromosomal imbalances such as trisomy confined to the placenta; however, the impact of smaller copy number variants (CNVs) has not yet been adequately addressed. In this study, we confirm the importance of placental aneuploidy, and assess the potential contribution of CNVs to fetal growth.

Methods

We used molecular-cytogenetic approaches to identify aneuploidy in placentas from 101 infants born small-for-gestational age (SGA), typically used as a surrogate for FGR, and from 173 non-SGA controls from uncomplicated pregnancies. We confirmed aneuploidies and assessed mosaicism by microsatellite genotyping. We then profiled CNVs using high-resolution microarrays in a subset of 53 SGA and 61 control euploid placentas, and compared the load, impact, gene enrichment and clinical relevance of CNVs between groups. Candidate CNVs were confirmed using quantitative PCR.

Results

Aneuploidy was over tenfold more frequent in SGA-associated placentas compared to controls (11.9% vs. 1.1%; p = 0.0002, OR = 11.4, 95% CI 2.5–107.4), was confined to the placenta, and typically involved autosomes, whereas only sex chromosome abnormalities were observed in controls. We found no significant difference in CNV load or number of placental-expressed or imprinted genes in CNVs between SGA and controls, however, a rare and likely clinically-relevant germline CNV was identified in 5.7% of SGA cases. These CNVs involved candidate genes INHBB, HSD11B2, CTCF, and CSMD3.

Conclusions

We conclude that placental genomic imbalances at the cytogenetic and submicroscopic level may underlie up to ~ 18% of SGA cases in our population. This work contributes to the understanding of the underlying causes of placental insufficiency and FGR, which is important for counselling and prediction of long term outcomes for affected cases.

Cell-specific characterization of the placental methylome

BACKGROUND

DNA methylation (DNAm) profiling has emerged as a powerful tool for characterizing the placental methylome. However, previous studies have focused primarily on whole placental tissue, which is a mixture of epigenetically distinct cell populations. Here, we present the first methylome-wide analysis of first trimester (n = 9) and term (n = 19) human placental samples of four cell populations: trophoblasts, Hofbauer cells, endothelial cells, and stromal cells, using the Illumina EPIC methylation array, which quantifies DNAm at > 850,000 CpGs.

RESULTS

The most distinct DNAm profiles were those of placental trophoblasts, which are central to many pregnancy-essential functions, and Hofbauer cells, which are a rare fetal-derived macrophage population. Cell-specific DNAm occurs at functionally-relevant genes, including genes associated with placental development and preeclampsia. Known placental-specific methylation marks, such as those associated with genomic imprinting, repetitive element hypomethylation, and placental partially methylated domains, were found to be more pronounced in trophoblasts and often absent in Hofbauer cells. Lastly, we characterize the cell composition and cell-specific DNAm dynamics across gestation.

CONCLUSIONS

Our results provide a comprehensive analysis of DNAm in human placental cell types from first trimester and term pregnancies. This data will serve as a useful DNAm reference for future placental studies, and we provide access to this data via download from GEO (GSE159526), through interactive exploration from the web browser ( https://robinsonlab.shinyapps.io/Placental_Methylome_Browser/ ), and through the R package planet, which allows estimation of cell composition directly from placental DNAm data.

Let-7a inhibits Bcl-xl and YAP1 expression to induce apoptosis of trophoblast cells in early-onset severe preeclampsia

Dysregulation of the MicroRNA (miR) Let-7 family has been implicated in preeclampsia (PE). Abnormal trophoblast cell proliferation and apoptosis associate with the pathogenesis of PE. The present study was designed to test the hypothesis whether let-7a could regulate the biological functions of trophoblasts and explore the mechanism how it works in the development of early-onset severe PE. The putative target genes Bcl-xl and YAP1 of let-7a were verified by luciferase assay. The roles of let-7a, Bcl-xl and YAP1 in regulating JEG-3 cell functions were examined by altering their expression with mimic, overexpression plasmids or siRNAs. The methylation status of let-7a-3 in PE was assessed by methylation-specific and bisulfite sequencing PCR assays. JEG-3 cells were treated with DNA methyltransferase inhibitor to analyze whether let-7a-3 demethylation functioned in PE. Tumor growth and cell apoptosis were measured from nude mice inoculated with JEG-3 cells overexpressing let-7a. The results revealed let-7a was highly expressed in early-onset severe PE and let-7a-3 presented a low methylation level. Functionally, let-7a upregulation could inhibit the viability and cell cycle progression but induce the apoptosis of JEG-3 cells. Bcl-xl and YAP1, target genes of let-7a, could rescue cell apoptosis induced by let-7a. The demethylation of let-7a-3 was also observed to elevate the expression of let-7a and enhance JEG-3 cell apoptosis. Let-7a inhibited tumorigenic ability of JEG-3 cells and enhanced cell apoptosis in vivo. Altogether, let-7a could enhance cell apoptosis in trophoblasts through downregulation of Bcl-xl and YAP1, which suggests that let-7a might be a key regulator in the progression of PE.

Comprehensive Analysis of Differently Expressed and Methylated Genes in Preeclampsia

Preeclampsia (PE) is one of the mainly caused maternal and infant incidences and mortalities worldwide. However, the mechanisms underlying PE remained largely unclear. The present study identified 1716 high expressions of gene and 2705 low expressions of gene using GSE60438 database, and identified 7087 hypermethylated and 15120 hypomethylated genes in preeclampsia using GSE100197. Finally, 536 upregulated genes with hypomethylation and 322 downregulated genes with hypermethylation were for the first time revealed in PE. Gene Ontology (GO) analysis revealed that these genes were associated with peptidyl-tyrosine phosphorylation, skeletal system development, leukocyte migration, transcription regulation, T cell receptor and IFN-γ-involved pathways, innate immune response, signal transduction, cell adhesion, angiogenesis, and hemopoiesis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis demonstrated that aberrantly methylated differentially expressed genes were involved in regulating adherens junction, pluripotency of stem cell regulation, immune processing, T cell receptor and NF-κB pathways, HTLV-I and HSV infections, leishmaniasis, and NK-induced cytotoxicity. Protein-protein interaction (PPI) network analysis identified several hub networks and key genes, including MAPK8, CCNF, CDC23, ABL1, NF1, UBE2E3, CD44, and PIK3R1. We hope these findings will draw more attention to these hub genes in future PE studies.

Global DNA methylation in placental tissues from pregnant with preeclampsia: A systematic review and pathway analysis

Pre-eclampsia (PE) is the major cause of fetal and maternal mortality and can be classified according to gestational age of onset into early-onset (EOPE, <34 weeks of gestation) and late- (LOPE, ≥34 weeks of gestation). DNA methylation (DNAm) may help to understand the abnormal placentation in PE. Therefore, we performed a systematic review to assess the role of global DNAm on pathophysiology of PE, focused on fetal and maternal tissues of placenta from pregnant with PE, including EOPE and LOPE. We searched the databases EMBASE, Medline/PubMed, Cochrane Central Register of Controlled Trials, Scopus, Lilacs, Scielo and Google Scholar, and followed the MOOSE guidelines. Moreover, we performed pathway analysis with the overlapping genes from the included studies. Twelve out of 24 included studies in the qualitative analysis considered the classification into EOPE and LOPE. We did not found heterogeneity in the criteria used for diagnosis of PE, and a few studies evaluated whether confounding factors would influence placental DNAm. Fourteen out of 24 included studies showed hypomethylation in placental tissue from pregnant with PE compared to controls. The differences in DNAm are specific to genes or differentially methylated regions, and more evident in EOPE and preterm PE compared to controls, rather than LOPE and term PE. The overlapping genes from included studies revealed pathways relevant to pathophysiology of PE. Our findings highlighted the heterogeneous results of the included studies, mainly focused on North America and China. Replication studies in different populations should use the same placental tissues, techniques to assess DNAm and pipelines for bioinformatic analysis.

Systematic review supports the role of DNA methylation in the pathophysiology of preeclampsia: a call for analytical and methodological standardization

BACKGROUND

Studies have recently examined the role of epigenetic mechanisms in preeclampsia pathophysiology. One commonly examined epigenetic process is DNA methylation. This heritable epigenetic marker is involved in many important cellular functions. The aim of this study was to establish the association between DNA methylation and preeclampsia and to critically appraise the roles of major study characteristics that can significantly impact the association between DNA methylation and preeclampsia.

MAIN BODY

A systematic review was performed by searching PubMed, Web of Science, and EMBASE for original research articles published over time, until May 31, 2019 in English. Eligible studies compared DNA methylation levels in pregnant women with vs. without preeclampsia. Ninety articles were included. Epigenome-wide studies identified hundreds of differentially methylated places/regions in preeclamptic patients. Hypomethylation was the predominant finding in studies analyzing placental tissue (14/19), while hypermethylation was detected in three studies that analyzed maternal white blood cells (3/3). In candidate gene studies, methylation alterations for a number of genes were found to be associated with preeclampsia. A greater number of differentially methylated genes was found when analyzing more severe preeclampsia (70/82), compared to studies analyzing less severe preeclampsia vs. controls (13/27). A high degree of heterogeneity existed among the studies in terms of methodological study characteristics including design (study design, definition of preeclampsia, control group, sample size, confounders), implementation (biological sample, DNA methylation method, purification of DNA extraction, and validation of methylation), analysis (analytical method, batch effect, genotyping, and gene expression), and data presentation (methylation quantification measure, measure of variability, reporting). Based on the results of this review, we provide recommendations for study design and analytical approach for further studies.

CONCLUSIONS

The findings from this review support the role of DNA methylation in the pathophysiology of preeclampsia. Establishing field-wide methodological and analytical standards may increase value and reduce waste, allowing researchers to gain additional insights into the role of DNA methylation in the pathophysiology of preeclampsia.

Identification and characterization of methylation-mediated transcriptional dysregulation dictate methylation roles in preeclampsia

Background

Preeclampsia (PE) is a heterogeneous, hypertensive disorder of pregnancy, with no robust biomarkers or effective treatments. PE increases the risk of poor outcomes for both the mother and the baby. Methylation-mediated transcriptional dysregulation motifs (methTDMs) could contribute the PE development. However, precise functional roles of methTDMs in PE have not been globally described.

Methods

Here, we develop a comprehensive and computational pipeline to identify PE-specific methTDMs following TF, gene, methylation expression profile, and experimentally verified TF-gene interactions.

Results

The regulation patterns of methTDMs are multiple and complex in PE and contain relax inhibition, intensify inhibition, relax activation, intensify activation, reverse activation, and reverse inhibition. A core module is extracted from global methTDM network to further depict the mechanism of methTDMs in PE. The common and specific features of any two kinds of regulation pattern are also analyzed in PE. Some key methylation sites, TFs, and genes such as IL2RG are identified in PE. Functional analysis shows that methTDMs are associated with immune-, insulin-, and NK cell-related functions. Drug-related network identifies some key drug repurposing candidates such as NADH.

Conclusion

Collectively, the study highlighted the effect of methylation on the transcription process in PE. MethTDMs could contribute to identify specific biomarkers and drug repurposing candidates for PE.

Reciprocal upregulation of hypoxia-inducible factor-1α and persistently enhanced placental adenosine signaling contribute to the pathogenesis of preeclampsia

Recent evidence indicates that elevated placental adenosine signaling contributes to preeclampsia (PE). However, the molecular basis for the chronically enhanced placental adenosine signaling in PE remains unclear. Here, we report that hypoxia-inducible factor-1α (HIF-1α) is crucial for the enhancement of placental adenosine signaling. Utilizing a pharmacologic approach to reduce placental adenosine levels, we found that enhanced adenosine underlies increased placental HIF-1α in an angiotensin receptor type 1 receptor agonistic autoantibody (AT₁ -AA)-induced mouse model of PE. Knockdown of placental HIF-1α in vivo suppressed the accumulation of adenosine and increased ecto-5'-nucleotidase (CD73) and adenosine A_2B receptor (ADORA2B) in the placentas of PE mouse models induced by AT₁ -AA or LIGHT, a TNF superfamily cytokine (TNFSF14). Human in vitro studies using placental villous explants demonstrated that increased HIF-1α resulting from ADORA2B activation facilitates the induction of CD73, ADORA2B, and FLT-1 expression. Overall, we demonstrated that (a) elevated placental HIF-1α by AT₁ -AA or LIGHT upregulates CD73 and ADORA2B expression and (b) enhanced adenosine signaling through upregulated ADORA2B induces placental HIF-1α expression, which creates a positive feedback loop that promotes FLT-1 expression leading to disease development. Our results suggest that adenosine-based therapy targeting the malicious cycle of placental adenosine signaling may elicit therapeutic effects on PE.

Modulation of Placental Gene Expression in Small-for-Gestational-Age Infants

Small-for-gestational-age (SGA) infants are fetuses that have not reached their genetically programmed growth potential. Low birth weight predisposes these infants to an increased risk of developing cardiovascular, metabolic and neurodevelopmental conditions in later life. However, our understanding of how this pathology occurs is currently incomplete. Previous research has focused on understanding the transcriptome, epigenome and bacterial signatures separately. However, we hypothesise that interactions between moderators of gene expression are critical to understanding fetal growth restriction. Through a review of the current literature, we identify that there is evidence of modulated expression/methylation of the placental genome and the presence of bacterial DNA in the placental tissue of SGA infants. We also identify that despite limited evidence of the interactions between the above results, there are promising suggestions of a relationship between bacterial signatures and placental function. This review aims to summarise the current literature concerning fetal growth from multiple avenues and propose a novel relationship between the placental transcriptome, methylome and bacterial signature that, if characterised, may be able to improve our current understanding of the placental response to stress and the aetiology of growth restriction.

Integrated analysis of the transcriptome-wide m6A methylome in preeclampsia and healthy control placentas

N6-methyladenosine (m6A) is the most prevalent modification in eukaryotic mRNA and potential regulatory functions of m6A have been shown by mapping the RNA m6A modification landscape. m6A modification in active gene regulation manifests itself as altered methylation profiles. The number of reports regarding to the profiling of m6A modification and its potential role in the placenta of preeclampsia (PE) is small. In this work, placental samples were collected from PE and control patients. Expression of m6A-related genes was investigated using quantitative real-time PCR. MeRIP-seq and RNA-seq were performed to detect m6A methylation and mRNA expression profiles. Gene ontology (GO) functional and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were also conducted to explore the modified genes and their clinical significance. Our findings show that METTL3 and METTL14 were up-regulated in PE. In total, 685 m6A peaks were differentially expressed as determined by MeRIP-seq. Altered peaks of m6A-modified transcripts were primarily associated with nitrogen compound metabolic process, positive regulation of vascular-associated smooth muscle cell migration, and endoplasmic reticulum organisation. The m6A hyper-methylated genes of Wnt/β-catenin signalling pathway, mTOR signalling pathway, and several cancer-related pathways may contribute to PE. We also verified that the significant increase of HSPA1A mRNA and protein expression was regulated by m6A modification, suggesting m6A plays a key role in the regulation of gene expression. Our data provide novel information regarding m6A modification alterations in PE and help our understanding of the pathogenesis of PE.

Expression of ACKR2 in placentas from different types of preeclampsia

OBJECTIVE

The purpose of this study was to investigate the expression of atypical chemokine receptor 2 (ACKR2, D6) in different types of preeclampsia (PE) and its effects on trophoblast proliferation and apoptosis.

METHODS

The subjects were divided into four groups: early-onset PE group (EOPE, n = 30), late-onset PE group (LOPE, n = 30), preterm birth group (PB, n = 30), and normal group (N, n = 30). The expression of ACKR2 in placentas was evaluated using immunohistochemistry, qRT-PCR, and Western blot. The trophoblast cell line JAR was cultured to detect the expression of ACKR2 after simulating hypoxic conditions with cobalt chloride (CoCl₂). The effects on cell proliferation, apoptosis, and expression of the chemokine CCL2 were analyzed after silencing ACKR2 with siRNA.

RESULTS

ACKR2 was decreased in placentas of EOPE and PB groups at the protein and mRNA level，compared to the normal group. No statistical differences were found between EOPE and PB groups, or between LOPE and normal groups. In our in vitro work, we found that the expression of ACKR2 decreased after treatment with 150 μmol/L, 200 μmol/L, and 250 μmol/L of CoCl₂. After ACKR2 was silenced, the degree of cellular proliferation decreased, while apoptosis and CCL2 expression increased.

CONCLUSION

The changes of ACKR2 expression in placentas of PE may be related to gestational weeks. Hypoxia inhibits the expression of ACKR2 in placentas. Abnormal expression of ACKR2 in PE may lead to dysfunction of trophoblast, and ACKR2 is an essential player in the immunoregulation of the placental chemokine CCL2.

Quality control measures for placental sample purity in DNA methylation array analyses

The purity of tissue samples can affect the accuracy and utility of DNA methylation array analyses. This is particularly important for the placenta which is globally hypomethylated compared to other tissues. Placental villous tissue from early pregnancy terminations can be difficult to separate from non-villous tissue, resulting in potentially inaccurate results. We used several methods to identify mixed placenta samples using DNA methylation array datasets from our laboratory and those contained in the NCBI GEO database, highlighting the importance of determining sample purity during quality control processes.

The significance of the placental genome and methylome in fetal and maternal health

The placenta is a crucial organ for supporting a healthy pregnancy, and defective development or function of the placenta is implicated in a number of complications of pregnancy that affect both maternal and fetal health, including maternal preeclampsia, fetal growth restriction, and spontaneous preterm birth. In this review, we highlight the role of the placental genome in mediating fetal and maternal health by discussing the impact of a variety of genetic alterations, from large whole-chromosome aneuploidies to single-nucleotide variants, on placental development and function. We also discuss the placental methylome in relation to its potential applications for refining diagnosis, predicting pathology, and identifying genetic variants with potential functional significance. We conclude that understanding the influence of the placental genome on common placental-mediated pathologies is critical to improving perinatal health outcomes.

Considerations when processing and interpreting genomics data of the placenta

The application of genomic approaches to placental research has opened exciting new avenues to help us understand basic biological properties of the placenta, improve prenatal screening/diagnosis, and measure effects of in utero exposures on child health outcomes. In the last decade, such large-scale genomic data (including epigenomics and transcriptomics) have become more easily accessible to researchers from many disciplines due to the increasing ease of obtaining such data and the rapidly evolving computational tools available for analysis. While the potential of large-scale studies has been widely promoted, less attention has been given to some of the challenges associated with processing and interpreting such data. We hereby share some of our experiences in assessing data quality, reproducibility, and interpretation in the context of genome-wide studies of the placenta, with the aim to improve future studies. There is rarely a single "best" approach, as that can depend on the study question and sample cohort. However, being consistent, thoroughly assessing potential confounders in the data, and communicating key variables in the methods section of the manuscript are critically important to help researchers to collaborate and build on each other's work.

Accurate ethnicity prediction from placental DNA methylation data

Background

The influence of genetics on variation in DNA methylation (DNAme) is well documented. Yet confounding from population stratification is often unaccounted for in DNAme association studies. Existing approaches to address confounding by population stratification using DNAme data may not generalize to populations or tissues outside those in which they were developed. To aid future placental DNAme studies in assessing population stratification, we developed an ethnicity classifier, PlaNET (Placental DNAme Elastic Net Ethnicity Tool), using five cohorts with Infinium Human Methylation 450k BeadChip array (HM450k) data from placental samples that is also compatible with the newer EPIC platform.

Results

Data from 509 placental samples were used to develop PlaNET and show that it accurately predicts (accuracy = 0.938, kappa = 0.823) major classes of self-reported ethnicity/race (African: n = 58, Asian: n = 53, Caucasian: n = 389), and produces ethnicity probabilities that are highly correlated with genetic ancestry inferred from genome-wide SNP arrays (> 2.5 million SNP) and ancestry informative markers (n = 50 SNPs). PlaNET’s ethnicity classification relies on 1860 HM450K microarray sites, and over half of these were linked to nearby genetic polymorphisms (n = 955). Our placental-optimized method outperforms existing approaches in assessing population stratification in placental samples from individuals of Asian, African, and Caucasian ethnicities.

Conclusion

PlaNET provides an improved approach to address population stratification in placental DNAme association studies. The method can be applied to predict ethnicity as a discrete or continuous variable and will be especially useful when self-reported ethnicity information is missing and genotyping markers are unavailable.

Electronic supplementary material

The online version of this article (10.1186/s13072-019-0296-3) contains supplementary material, which is available to authorized users.

Human placental methylome in the interplay of adverse placental health, environmental exposure, and pregnancy outcome

The placenta is the interface between maternal and fetal circulations, integrating maternal and fetal signals to selectively regulate nutrient, gas, and waste exchange, as well as secrete hormones. In turn, the placenta helps create the in utero environment and control fetal growth and development. The unique epigenetic profile of the human placenta likely reflects its early developmental separation from the fetus proper and its role in mediating maternal–fetal exchange that leaves it open to a range of exogenous exposures in the maternal circulation. In this review, we cover recent advances in DNA methylation in the context of placental function and development, as well as the interaction between the pregnancy and the environment.

Placental microRNAs in pregnancies with early onset intrauterine growth restriction and preeclampsia: potential impact on gene expression and pathophysiology

BACKGROUND

A normally developed placenta is integral to a successful pregnancy. Preeclampsia (PE) and intrauterine growth restriction (IUGR) are two common pregnancy related complications that maybe a result of abnormal placental development. Placental microRNAs (miRNAs) have been investigated as potential biomarkers for these complications, as they may play a role in placental development and pathophysiology by influencing gene expression. The purpose of this study is to utilize next-generation sequencing to determine miRNA and gene expression in human placental (chorionic villous) samples from three distinct patient groups with early-onset (EO) PE, IUGR, or PE + IUGR.

METHODS

Placental tissues were collected from four patient groups (control [N = 21], EO-PE [N = 20], EO-IUGR [N = 18], and EO-PE + IUGR [N = 20]), and total RNA was used for miRNA and RNA sequencing on the Illumina Hiseq2000 platform. For stringent differential expression analysis multiple analysis programs were used to analyze both expression datasets in each patient group compared to gestational age-matched controls.

RESULTS

Analysis revealed miRNAs and genes that are disease-specific, as well as others that were common between disease groups, which suggests common underlying placental pathologies in EO-PE and EO-IUGR. More specifically, 6 miRNAs and 22 genes were identified to be differentially expressed in all three patient groups. In addition, integrative analysis between the miRNA and gene expression datasets revealed candidate gene targets for miRNAs of interest.

CONCLUSIONS

Integration of miRNA and RNA profiling in the same three subgroups of pregnancy complications, provides an alternate level of molecular information, in addition it can be used to better understand both unique and common molecular mechanisms involved in the pathophysiology of these diseases.

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

The human pan-tissue epigenetic clock is widely used for estimating age across the entire lifespan, but it does not lend itself well to estimating gestational age (GA) based on placental DNAm methylation (DNAm) data. We replicate previous findings demonstrating a strong correlation between GA and genome-wide DNAm changes. Using substantially more DNAm arrays (n=1,102 in the training set) than a previous study, we present three new placental epigenetic clocks: 1) a robust placental clock (RPC) which is unaffected by common pregnancy complications (e.g., gestational diabetes, preeclampsia), and 2) a control placental clock (CPC) constructed using placental samples from pregnancies without known placental pathology, and 3) a refined RPC for uncomplicated term pregnancies. These placental clocks are highly accurate estimators of GA based on placental tissue; e.g., predicted GA based on RPC is highly correlated with actual GA (r>0.95 in test data, median error less than one week). We show that epigenetic clocks derived from cord blood or other tissues do not accurately estimate GA in placental samples. While fundamentally different from Horvath's pan-tissue epigenetic clock, placental clocks closely track fetal age during development and may have interesting applications.

The Role of Epigenetics in Placental Development and the Etiology of Preeclampsia

In this review, we comprehensively present the function of epigenetic regulations in normal placental development as well as in a prominent disease of placental origin, preeclampsia (PE). We describe current progress concerning the impact of DNA methylation, non-coding RNA (with a special emphasis on long non-coding RNA (lncRNA) and microRNA (miRNA)) and more marginally histone post-translational modifications, in the processes leading to normal and abnormal placental function. We also explore the potential use of epigenetic marks circulating in the maternal blood flow as putative biomarkers able to prognosticate the onset of PE, as well as classifying it according to its severity. The correlation between epigenetic marks and impacts on gene expression is systematically evaluated for the different epigenetic marks analyzed.

Altered levels of placental miR-338-3p and miR-518b are associated with acute chorioamnionitis and IL6 genotype

Placental-derived miRNAs are attractive candidates as biomarkers of placental health, but their associations with specific pathologies, such as acute chorioamnionitis (aCA), are not well explored. Samples of chorionic villi from 57 placentas (33 aCA and 24 non-aCA) were analyzed. Expression was quantified for six candidate miRNAs (miR-146a, miR-210, miR-223, miR-338-3p, miR-411, and miR-518b), using quantitative real-time PCR. miR-518b and miR-338-3p were differentially expressed between aCA cases and non-aCA cases (Bonferroni-corrected p < 0.05). Further, we observed that placental miR-518b expression was associated with an IL6 SNP (rs1800796), a polymorphism we previously reported as a risk-conferring variant for aCA.

Epigenome-wide association data implicate fetal/maternal adaptations contributing to clinical outcomes in preeclampsia

Aim: To investigate the changes of placental DNA methylome in preeclampsia (PE). Materials & methods: We performed an epigenome-wide association study in a Chinese cohort and six published datasets consisting of 335 samples in total. Results & conclusion: Numerous consistently hypomethylated probes were associated with early-onset PE in different populations, with 2125 reaching epigenome-wide significance. The validated probes were enriched for cytosine-phosphate-guanine dinucleotide (CpG) sites partially methylated and located in genes related to trophoblast fusion. The methylation levels of the validated probes were associated with clinical severity, while the intermediate samples showed antagonistic fetal/maternal outcomes. The DNA methylation patterns of PE and clinically relevant obstetrical syndromes suggested partially common pathophysiologies and complex maternal/fetal adaptive responses contributing to variable clinical outcomes.

Association of a placental Interleukin-6 genetic variant (rs1800796) with DNA methylation, gene expression and risk of acute chorioamnionitis

BACKGROUND

Acute chorioamnionitis (aCA), inflammation of the placenta and fetal membranes, is a frequently reported lesion in preterm deliveries. Genetic variants in innate immune system genes such as Interleukin-6 (IL6) may contribute to the placenta's inflammatory response, thus predisposing some pregnancies to aCA. These genetic variants may modulate molecular processes such as DNA methylation and gene expression, and in turn might affect susceptibility to aCA. Currently, there is remarkably little research on the role of fetal (placental) genetic variation in aCA. We aimed to explore the associations between genetic variants in candidate immune-system genes and susceptibility towards inflammatory responses in the placenta, which is linked to a strong inflammatory response in the newborn.

METHODS

DNA samples from 269 placentas (72 aCA cases, 197 non-aCA cases) were collected for this study. Samples were genotyped at 55 ancestry informative markers (AIMs) and 16 additional single nucleotide polymorphisms (SNPs) in 12 candidate innate immune system genes using the Sequenom iPLEX Gold Assay. Publicly available datasets were used to obtain DNA methylation (GSE100197, GSE74738, GSE115508, GSE44667, GSE98224) and gene expression data (GSE44711, GSE98224).

RESULTS

Differences in IL6 placental allele frequencies were associated with aCA (rs1800796, p = 0.04) with the CC genotype specifically implicated (OR = 3.1; p = 0.02). In a subset of the placental samples (n = 67; chorionic villi), we showed that the IL6 SNP (rs1800796) was associated with differential DNA methylation in five IL6-related CpG sites (cg01770232, cg02335517, cg07998387, cg13104385, and cg0526589), where individuals with a CC genotype showed higher DNA methylation levels than individuals carrying the GG genotype. Using two publicly available datasets, we observed that the DNA methylation levels at cg01770232 negatively correlated with IL6 gene expression in the placenta (r = - 0.67, p < 0.004; r = - 0.56, p < 2.937e-05).

CONCLUSIONS

We demonstrated that the minor C allele at the IL6 SNP (rs1800796), which is largely limited to East Asian populations, is associated with the presence of aCA. This SNP was associated with increased DNA methylation at a nearby MEPC2 binding site, which was also associated with decreased expression of IL6 in the placenta. Decreased expression of IL6 may increase vulnerability to microbial infection. Additional studies are required to confirm this association in Asian populations with larger sample sizes.

DNA methylation profiling of acute chorioamnionitis-associated placentas and fetal membranes: insights into epigenetic variation in spontaneous preterm births

BACKGROUND

Placental inflammation, often presenting as acute chorioamnionitis (aCA), is commonly associated with preterm birth. Preterm birth can have both immediate and long-term adverse effects on the health of the baby. Developing biomarkers of inflammation in the placenta can help to understand its effects and potentially lead to new approaches for rapid prenatal diagnosis of aCA. We aimed to characterize epigenetic variation associated with aCA in placenta (chorionic villi) and fetal membranes (chorion and amnion) to better understand how aCA may impact processes that lead to preterm birth. This study lays the groundwork for development of novel biomarkers for aCA.

METHODS

Samples from 44 preterm placentas (chorionic villi) as well as matched chorion and amnion for 16 of these cases were collected for this study. These samples were profiled using the Illumina Infinium HumanMethylation850 BeadChip to measure DNA methylation (DNAm) at 866,895 CpGs across the genome. An additional 78 placental samples were utilized to independently validate the array findings by pyrosequencing.

RESULTS

Using a false discovery rate of < 0.15 and average group difference in DNAm of > 0.05, 66 differentially methylated (DM) CpG sites were identified between aCA cases and non-aCA cases in chorionic villi. For the majority of these 66 DM CpGs, the DNAm profile of the aCA cases as compared to the non-aCA cases trended in the direction of the blood cell DNAm. Interestingly, neutrophil-specific DNAm signatures, but not those associated with other immune cell types, were capable of separating aCA cases from the non-aCA cases.

CONCLUSIONS

Our results suggest that aCA-associated placentas showed altered DNAm signatures that were not observed in the absence of aCA. This DNAm profile is consistent with the activation of the innate immune response in the placenta and/or reflect increase in neutrophils as a response to inflammation.

No evidence for association of MTHFR 677C>T and 1298A>C variants with placental DNA methylation

Background

5,10-Methylenetetrahydrofolate reductase (MTHFR) is a key enzyme in one-carbon metabolism that ensures the availability of methyl groups for methylation reactions. Two single-nucleotide polymorphisms (SNPs) in the MTHFR gene, 677C>T and 1298A>C, result in a thermolabile enzyme with reduced function. These variants, in both the maternal and/or fetal genes, have been associated with pregnancy complications including miscarriage, neural tube defects (NTDs), and preeclampsia (PE), perhaps due to altered capacity for DNA methylation (DNAm). In this study, we assessed the association between MTHFR 677TT and 1298CC genotypes and risk of NTDs, PE, or normotensive intrauterine growth restriction (nIUGR). Additionally, we assessed whether these high-risk genotypes are associated with altered DNAm in the placenta.

Results

In 303 placentas screened for this study, we observed no significant association between the occurrence of NTDs (N = 55), PE (early-onset: N = 28, late-onset: N = 20), or nIUGR (N = 21) and placental (fetal) MTHFR 677TT or 1298CC genotypes compared to healthy pregnancies (N = 179), though a trend of increased 677TT genotype in PE/IUGR together was observed (OR 2.53, p = 0.048). DNAm was profiled in 10 high-risk 677 (677TT + 1298AA), 10 high-risk 1298 (677CC + 1298CC), and 10 reference (677CC + 1298AA) genotype placentas. Linear modeling identified no significantly differentially methylated sites between high-risk 677 or 1298 and reference placentas at a false discovery rate < 0.05 and Δβ ≥ 0.05 using the Illumina Infinium HumanMethylation450 BeadChip. Using a differentially methylated region analysis or separating cytosine-guanine dinucleotides (CpGs) by CpG density to reduce multiple comparisons also did not identify differential methylation. Additionally, there was no consistent evidence for altered methylation of repetitive DNA between high-risk and reference placentas.

Conclusions

We conclude that large-scale, genome-wide disruption in DNAm does not occur in placentas with the high-risk MTHFR 677TT or 1298CC genotypes. Furthermore, there was no evidence for an association of the 1298CC genotype and only a tendency to higher 677TT in pregnancy complications of PE/IUGR. This may be due to small sample sizes or folate repletion in our Canadian population attenuating effects of the high-risk MTHFR variants. However, given our results and the conflicting results in the literature, investigations into alternative mechanisms that may explain the link between MTHFR variants and pregnancy complications, or in populations at risk of folate deficiencies, are warranted.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0468-1) contains supplementary material, which is available to authorized users.

Epigenetic regulation of placental gene expression in transcriptional subtypes of preeclampsia

Background

Preeclampsia (PE) is a heterogeneous, hypertensive disorder of pregnancy, with no robust biomarkers or effective treatments. We hypothesized that this heterogeneity is due to the existence of multiple subtypes of PE and, in support of this hypothesis, we recently identified five clusters of placentas within a large gene expression microarray dataset (N = 330), of which four (clusters 1, 2, 3, and 5) contained a substantial number of PE samples. However, while transcriptional analysis of placentas can subtype patients, we propose that the addition of epigenetic information could discern gene regulatory mechanisms behind the distinct PE pathologies, as well as identify clinically useful potential biomarkers.

Results

We subjected 48 of our samples from transcriptional clusters 1, 2, 3, and 5 to Infinium HumanMethylation450 arrays. Samples belonging to transcriptional clusters 1–3 still showed visible relationships to each other by methylation, but cluster 5, with known chromosomal abnormalities, no longer formed a cohesive group. Within transcriptional clusters 2 and 3, controlling for fetal sex and gestational age in the identification of differentially methylated sites, compared to the healthier cluster 1, dramatically reduced the number of significant sites, but increased the percentage that demonstrated a strong linear correlation with gene expression (from 5% and 2% to 9% and 8%, respectively). Locations exhibiting a positive relationship between methylation and gene expression were most frequently found in CpG open sea enhancer regions within the gene body, while those with a significant negative correlation were often annotated to the promoter in a CpG shore region. Integrated transcriptome and epigenome analysis revealed modifications in TGF-beta signaling, cell adhesion, oxidative phosphorylation, and metabolism pathways in cluster 2 placentas, and aberrations in antigen presentation, allograft rejection, and cytokine-cytokine receptor interaction in cluster 3 samples.

Conclusions

Overall, we have established DNA methylation alterations underlying a portion of the transcriptional development of “canonical” PE in cluster 2 and “immunological” PE in cluster 3. However, a significant number of the observed methylation changes were not associated with corresponding changes in gene expression, and vice versa, indicating that alternate methods of gene regulation will need to be explored to fully comprehend these PE subtypes.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0463-6) contains supplementary material, which is available to authorized users.