Associations between placental CpG methylation of metastable epialleles and childhood body mass index across ages one, two and ten in the Extremely Low Gestational Age Newborns (ELGAN) cohort

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.

Epigenetic associations in HPA axis genes related to bronchopulmonary dysplasia and antenatal steroids

BACKGROUND

Bronchopulmonary dysplasia (BPD), a common morbidity among very preterm infants, is associated with chronic disease and neurodevelopmental impairments. A hypothesized mechanism for these outcomes lies in altered glucocorticoid (GC) activity. We hypothesized that BPD and its treatments may result in epigenetic differences in the hypothalamic-pituitary-adrenal (HPA) axis, which is modulated by GC, and could be ascertained using an established GC risk score and DNA methylation (DNAm) of HPA axis genes.

METHODS

DNAm was quantified from buccal tissue (ECHO-NOVI) and from neonatal blood spots (ELGAN ECHO) via the EPIC microarray. Prenatal maternal characteristics, pregnancy complication, and neonatal medical complication data were collected from medical record review and maternal interviews.

RESULTS

The GC score was not associated with steroid exposure or BPD. However, six HPA genes involved in stress response regulation demonstrated differential methylation with antenatal steroid exposure; two CpGs within FKBP5 and POMC were differentially methylated with BPD severity. These findings were sex-specific in both cohorts; males had greater magnitude of differential methylation within these genes.

CONCLUSIONS

These findings suggest that BPD severity and antenatal steroids are associated with DNAm at some HPA genes in very preterm infants and the effects appear to be sex-, tissue-, and age-specific.

IMPACT

This study addresses bronchopulmonary dysplasia (BPD), an important health outcome among preterm neonates, and interrogates a commonly studied pathway, the hypothalamic-pituitary-adrenal (HPA) axis. The combination of BPD, the HPA axis, and epigenetic markers has not been previously reported. In this study, we found that BPD itself was not associated with epigenetic responses in the HPA axis in infants born very preterm; however, antenatal treatment with steroids was associated with epigenetic responses.

Metastable epialleles in humans

First identified in isogenic mice, metastable epialleles (MEs) are loci where the extent of DNA methylation (DNAm) is variable between individuals but correlates across tissues derived from different germ layers within a given individual. This property, termed systemic interindividual variation (SIV), is attributed to stochastic methylation establishment before germ layer differentiation. Evidence suggests that some putative human MEs are sensitive to environmental exposures in early development. In this review we introduce key concepts pertaining to human MEs, describe methods used to identify MEs in humans, and review their genomic features. We also highlight studies linking DNAm at putative human MEs to early environmental exposures and postnatal (including disease) phenotypes.

Prenatal exposure to triclosan assessed in multiple urine samples and placental DNA methylation

A previous study reported positive associations of maternal urinary concentrations of triclosan, a synthetic phenol with widespread exposure in the general population, with placental DNA methylation of male fetuses. Given the high number of comparisons performed in -omic research, further studies were needed to validate and extend on these findings. Using a cohort of male and female fetuses with repeated maternal urine samples to assess exposure, we studied the associations between triclosan and placental DNA methylation. We assessed triclosan concentrations in two pools of 21 urine samples collected among 395 women from the SEPAGES cohort. We used Infinium Methylation EPIC arrays to measure DNA methylation in placental biopsies collected at delivery. We performed a candidate study restricted to a set of candidate CpGs (n = 500) identified in a previous work as well as an exploratory epigenome-wide association study to investigate the associations between triclosan and differentially methylated probes and regions. Analyses were conducted on the whole population and stratified by child's sex. Mediation analysis was performed to test whether heterogeneity of placental tissue may mediate the observed associations. In the candidate approach, we confirmed 18 triclosan-associated genes when both sexes were considered. After stratification for child's sex, triclosan was associated with 72 genes in females and three in males. Most of the associations were positive and several CpGs mapped to imprinted genes: FBRSL1, KCNQ1, RHOBTB3, and SMOC1. A mediation effect by placental tissue heterogeneity was identified for most of the observed associations. In the exploratory analysis, we identified a few isolated associations in the sex-stratified analysis. In line with a previous study on male placentas, our approach revealed several positive associations between triclosan exposure and placental DNA methylation. Several identified loci mapped to imprinted genes.

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.

A multi-omic approach identifies an autism spectrum disorder (ASD) regulatory complex of functional epimutations in placentas from children born preterm

Children born preterm are at heightened risk of neurodevelopmental impairments, including Autism Spectrum Disorder (ASD). The placenta is a key regulator of neurodevelopmental processes, though the precise underlying molecular mechanisms remain unclear. Here, we employed a multi-omic approach to identify placental transcriptomic and epigenetic modifications related to ASD diagnosis at age 10, among children born preterm. Working with the extremely low gestational age (ELGAN) cohort, we hypothesized that a pro-inflammatory placental environment would be predictive of ASD diagnosis at age 10. Placental messenger RNA (mRNA) expression, CpG methylation, and microRNA (miRNA) expression were compared among 368 ELGANs (28 children diagnosed with ASD and 340 children without ASD). A total of 111 genes displayed expression levels in the placenta that were associated with ASD. Within these ASD-associated genes is an ASD regulatory complex comprising key genes that predicted ASD case status. Genes with expression that predicted ASD case status included Ewing Sarcoma Breakpoint Region 1 (EWSR1) (OR: 6.57 (95% CI: 2.34, 23.58)) and Bromodomain Adjacent To Zinc Finger Domain 2A (BAZ2A) (OR: 0.12 (95% CI: 0.03, 0.35)). Moreover, of the 111 ASD-associated genes, nine (8.1%) displayed associations with CpG methylation levels, while 14 (12.6%) displayed associations with miRNA expression levels. Among these, LRR Binding FLII Interacting Protein 1 (LRRFIP1) was identified as being under the control of both CpG methylation and miRNAs, displaying an OR of 0.42 (95% CI: 0.17, 0.95). This gene, as well as others identified as having functional epimutations, plays a critical role in immune system regulation and inflammatory response. In summary, a multi-omic approach was used to identify functional epimutations in the placenta that are associated with the development of ASD in children born preterm, highlighting future avenues for intervention.

Comparison of methanol fixation versus cryopreservation of the placenta for metabolomics analysis

Methods for collection of placental tissue at room temperature for metabolic profiling are described. Specimens were excised from the maternal side of the placenta and immediately flash frozen or fixed and stored for 1, 6, 12, 24, or 48 h in 80% methanol. Untargeted metabolic profiling was performed on both the methanol-fixed tissue and the methanol extract. Data were analyzed using Gaussian generalized estimating equations, two sample t-tests with false discovery rate (FDR) corrections, and principal components analysis. Methanol-fixed tissue samples and methanol extracts had a similar number of metabolites (p = 0.45, p = 0.21 in positive vs. negative ion mode). In positive ion mode, when compared to flash frozen tissue, both the methanol extract and methanol-fixed tissue (6 h) had a higher number of metabolites detected (146 additional metabolites, p_FDR = 0.020; 149 additional metabolites, p_FDR = 0.017; respectively), but these associations were not found in negative ion mode (all p_FDR ≥ 0.05). Principle components analysis demonstrated separation of the metabolite features in the methanol extract, but similarity between methanol-fixed tissue and flash frozen tissue. These results show that placental tissue samples collected in 80% methanol at room temperature can yield similar metabolic data to flash frozen specimens.

CpG methylation patterns in placenta and neonatal blood are differentially associated with neonatal inflammation

BACKGROUND

Infants born extremely premature are at increased risk for health complications later in life for which neonatal inflammation may be a contributing biological driver. Placental CpG methylation provides mechanistic information regarding the relationship between prenatal epigenetic programming, prematurity, neonatal inflammation, and later-in-life health.

METHODS

We contrasted CpG methylation in the placenta and neonatal blood spots in relation to neonatal inflammation in the Extremely Low Gestational Age Newborn (ELGAN) cohort. Neonatal inflammation status was based on the expression of six inflammation-related proteins, assessed as (1) day-one inflammation (DOI) or (2) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 postnatal weeks). Epigenome-wide CpG methylation was assessed in 354 placental samples and 318 neonatal blood samples.

RESULTS

Placental CpG methylation displayed the strongest association with ISSI (48 CpG sites) but was not associated with DOI. This was in contrast to CpG methylation in blood spots, which was associated with DOI (111 CpG sites) and not with ISSI (one CpG site).

CONCLUSIONS

Placental CpG methylation was strongly associated with ISSI, a measure of inflammation previously linked to later-in-life cognitive impairment, while day-one neonatal blood methylation was associated with DOI.

IMPACT

Neonatal inflammation increases the risk of adverse later-life outcomes, especially in infants born extremely preterm. CpG methylation in the placenta and neonatal blood spots were evaluated in relation to neonatal inflammation assessed via circulating proteins as either (i) day-one inflammation (DOI) or (ii) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 weeks). Tissue specificity was observed in epigenetic-inflammatory relationships: placental CpG methylation was associated with ISSI, neonatal blood CpG methylation was associated with DOI. Supporting the placental origins of disease framework, placental epigenetic patterns are associated with a propensity for ISSI in neonates.

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health.

Differential placental CpG methylation is associated with chronic lung disease of prematurity

BACKGROUND

Chronic lung disease (CLD) is the most common pulmonary morbidity in extremely preterm infants. It is unclear to what extent prenatal exposures influence the risk of CLD. Epigenetic variation in placenta DNA methylation may be associated with differential risk of CLD, and these associations may be dependent upon sex.

METHODS

Data were obtained from a multi-center cohort of infants born extremely preterm (<28 weeks' gestation) and an epigenome-wide approach was used to identify associations between placental DNA methylation and CLD (n = 423). Associations were evaluated using robust linear regression adjusting for covariates, with a false discovery rate of 0.05. Analyses stratified by sex were used to assess differences in methylation-CLD associations.

RESULTS

CLD was associated with differential methylation at 49 CpG sites representing 46 genes in the placenta. CLD was associated with differential methylation of probes within genes related to pathways involved in fetal lung development, such as p53 signaling and myo-inositol biosynthesis. Associations between CpG methylation and CLD differed by sex.

CONCLUSIONS

Differential placental methylation within genes with key roles in fetal lung development may reflect complex cell signaling between the placenta and fetus which mediate CLD risk. These pathways appear to be distinct based on fetal sex.

IMPACT

In extremely preterm infants, differential methylation of CpG sites within placental genes involved in pathways related to cell signaling, oxidative stress, and trophoblast invasion is associated with chronic lung disease of prematurity. DNA methylation patterns associated with chronic lung disease were distinctly based on fetal sex, suggesting a potential mechanism underlying dimorphic phenotypes. Mechanisms related to fetal hypoxia and placental myo-inositol signaling may play a role in fetal lung programming and the developmental origins of chronic lung disease. Continued research of the relationship between the placental epigenome and chronic lung disease could inform efforts to ameliorate or prevent this condition.

Placental genomics mediates genetic associations with complex health traits and disease

As the master regulator in utero, the placenta is core to the Developmental Origins of Health and Disease (DOHaD) hypothesis but is historically understudied. To identify placental gene-trait associations (GTAs) across the life course, we perform distal mediator-enriched transcriptome-wide association studies (TWAS) for 40 traits, integrating placental multi-omics from the Extremely Low Gestational Age Newborn Study. At $$P \; < \; 2.5\times {10}^{-6}$$ P < 2.5 × 10 − 6 , we detect 248 GTAs, mostly for neonatal and metabolic traits, across 176 genes, enriched for cell growth and immunological pathways. In aggregate, genetic effects mediated by placental expression significantly explain 4 early-life traits but no later-in-life traits. 89 GTAs show significant mediation through distal genetic variants, identifying hypotheses for distal regulation of GTAs. Investigation of one hypothesis in human placenta-derived choriocarcinoma cells reveal that knockdown of mediator gene EPS15 upregulates predicted targets SPATA13 and FAM214A, both associated with waist-hip ratio in TWAS, and multiple genes involved in metabolic pathways. These results suggest profound health impacts of placental genomic regulation in developmental programming across the life course.

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

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

CUE: CpG impUtation ensemble for DNA methylation levels across the human methylation450 (HM450) and EPIC (HM850) BeadChip platforms

DNA methylation at CpG dinucleotides is one of the most extensively studied epigenetic marks. With technological advancements, geneticists can profile DNA methylation with multiple reliable approaches. However, profiling platforms can differ substantially in the CpGs they assess, consequently hindering integrated analysis across platforms. Here, we present CpG impUtation Ensemble (CUE), which leverages multiple classical statistical and modern machine learning methods, to impute from the Illumina HumanMethylation450 (HM450) BeadChip to the Illumina HumanMethylationEPIC (HM850) BeadChip. Data were analysed from two population cohorts with methylation measured both by HM450 and HM850: the Extremely Low Gestational Age Newborns (ELGAN) study (n = 127, placenta) and the VA Boston Posttraumatic Stress Disorder (PTSD) genetics repository (n = 144, whole blood). Cross-validation results show that CUE achieves the lowest predicted root-mean-square error (RMSE) (0.026 in PTSD) and the highest accuracy (99.97% in PTSD) compared with five individual methods tested, including k-nearest-neighbours, logistic regression, penalized functional regression, random forest, and XGBoost. Finally, among all 339,033 HM850-only CpG sites shared between ELGAN and PTSD, CUE successfully imputed 289,604 (85.4%) sites, where success was defined as RMSE < 0.05 and accuracy >95% in PTSD. In summary, CUE is a valuable tool for imputing CpG methylation from the HM450 to HM850 platform.

Comparing the Predictivity of Human Placental Gene, microRNA, and CpG Methylation Signatures in Relation to Perinatal Outcomes

Molecular signatures are being increasingly integrated into predictive biology applications. However, there are limited studies comparing the overall predictivity of transcriptomic vs. epigenomic signatures in relation to perinatal outcomes. This study set out to evaluate mRNA and microRNA (miRNA) expression and cytosine-guanine dinucleotide (CpG) methylation signatures in human placental tissues and relate these to perinatal outcomes known to influence maternal/fetal health; namely, birth weight, placenta weight, placental damage, and placental inflammation. The following hypotheses were tested: (1) different molecular signatures will demonstrate varying levels of predictivity towards perinatal outcomes, and (2) these signatures will show disruptions from an example exposure (i.e., cadmium) known to elicit perinatal toxicity. Multi-omic placental profiles from 390 infants in the Extremely Low Gestational Age Newborns cohort were used to develop molecular signatures that predict each perinatal outcome. Epigenomic signatures (i.e., miRNA and CpG methylation) consistently demonstrated the highest levels of predictivity, with model performance metrics including R^2 (predicted vs. observed) values of 0.36-0.57 for continuous outcomes and balanced accuracy values of 0.49-0.77 for categorical outcomes. Top-ranking predictors included miRNAs involved in injury and inflammation. To demonstrate the utility of these predictive signatures in screening of potentially harmful exogenous insults, top-ranking miRNA predictors were analyzed in a separate pregnancy cohort and related to cadmium. Key predictive miRNAs demonstrated altered expression in association with cadmium exposure, including miR-210, known to impact placental cell growth, blood vessel development, and fetal weight. These findings inform future predictive biology applications, where additional benefit will be gained by including epigenetic markers.

Evidence for the placenta-brain axis: multi-omic kernel aggregation predicts intellectual and social impairment in children born extremely preterm

BACKGROUND

Children born extremely preterm are at heightened risk for intellectual and social impairment, including Autism Spectrum Disorder (ASD). There is increasing evidence for a key role of the placenta in prenatal developmental programming, suggesting that the placenta may, in part, contribute to origins of neurodevelopmental outcomes.

METHODS

We examined associations between placental transcriptomic and epigenomic profiles and assessed their ability to predict intellectual and social impairment at age 10 years in 379 children from the Extremely Low Gestational Age Newborn (ELGAN) cohort. Assessment of intellectual ability (IQ) and social function was completed with the Differential Ability Scales-II and Social Responsiveness Scale (SRS), respectively. Examining IQ and SRS allows for studying ASD risk beyond the diagnostic criteria, as IQ and SRS are continuous measures strongly correlated with ASD. Genome-wide mRNA, CpG methylation and miRNA were assayeds with the Illumina Hiseq 2500, HTG EdgeSeq miRNA Whole Transcriptome Assay, and Illumina EPIC/850 K array, respectively. We conducted genome-wide differential analyses of placental mRNA, miRNA, and CpG methylation data. These molecular features were then integrated for a predictive analysis of IQ and SRS outcomes using kernel aggregation regression. We lastly examined associations between ASD and the multi-omic-predicted component of IQ and SRS.

RESULTS

Genes with important roles in neurodevelopment and placental tissue organization were associated with intellectual and social impairment. Kernel aggregations of placental multi-omics strongly predicted intellectual and social function, explaining approximately 8% and 12% of variance in SRS and IQ scores via cross-validation, respectively. Predicted in-sample SRS and IQ showed significant positive and negative associations with ASD case-control status.

LIMITATIONS

The ELGAN cohort comprises children born pre-term, and generalization may be affected by unmeasured confounders associated with low gestational age. We conducted external validation of predictive models, though the sample size (N = 49) and the scope of the available out-sample placental dataset are limited. Further validation of the models is merited.

CONCLUSIONS

Aggregating information from biomarkers within and among molecular data types improves prediction of complex traits like social and intellectual ability in children born extremely preterm, suggesting that traits within the placenta-brain axis may be omnigenic.

Transcription Factor PLAGL1 Is Associated with Angiogenic Gene Expression in the Placenta

During pregnancy, the placenta is important for transporting nutrients and waste between the maternal and fetal blood supply, secreting hormones, and serving as a protective barrier. To better understand placental development, we must understand how placental gene expression is regulated. We used RNA-seq data and ChIP-seq data for the enhancer associated mark, H3k27ac, to study gene regulation in the mouse placenta at embryonic day (e) 9.5, when the placenta is developing a complex network of blood vessels. We identified several upregulated transcription factors with enriched binding sites in e9.5-specific enhancers. The most enriched transcription factor, PLAGL1 had a predicted motif in 233 regions that were significantly associated with vasculature development and response to insulin stimulus genes. We then performed several experiments using mouse placenta and a human trophoblast cell line to understand the role of PLAGL1 in placental development. In the mouse placenta, Plagl1 is expressed in endothelial cells of the labyrinth layer and is differentially expressed in placentas from mice with gestational diabetes compared to placentas from control mice in a sex-specific manner. In human trophoblast cells, siRNA knockdown significantly decreased expression of genes associated with placental vasculature development terms. In a tube assay, decreased PLAGL1 expression led to reduced cord formation. These results suggest that Plagl1 regulates overlapping gene networks in placental trophoblast and endothelial cells, and may play a critical role in placental development in normal and complicated pregnancies.