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.

Placental health is a key component to a successful pregnancy. Placental insufficiency (PI), inadequate nutrient delivery to the fetus, is associated with preeclampsia (PE), a maternal hypertensive disorder, and intrauterine growth restriction (IUGR), pathologically poor fetal growth. PI is more common in early-onset PE (EOPE) than late-onset PE (LOPE). However, the relationship between these disorders remains unclear. While DNA methylation (DNAm) alterations have been identified in PE and IUGR, these entities can overlap and few studies have analysed them separately. This study aims to utilize DNAm profiling to better understand the underlying placental variation associated with PE and IUGR. Placental samples from a discovery (43 controls, 22 EOPE, 18 LOPE, 11 IUGR) and validation cohort (15 controls, 22 EOPE, 11 LOPE) were evaluated using the Illumina HumanMethylation450 array. To account for gestational age (GA) effects, EOPE samples were compared with pre-term births of varying etiologies (GA <37 weeks). LOPE and IUGR were compared with term controls (GA >37 weeks). While 1703 sites were differentially methylated (DM) (FDR < 0.05, Δβ > 0.1) in EOPE, few changes were associated with LOPE (N = 5), or IUGR (N = 0). Of the 1703 EOPE sites, 599 validated in the second cohort. Using these 599 sites, both cohorts clustered into three distinct groups. Interestingly, LOPE samples diagnosed between 34 and 36 weeks with co-occurring IUGR clustered with the EOPE. DNAm profiling may provide an independent tool to refine clinical/pathological diagnoses into subgroups with more uniform pathology. Despite large changes observed in EOPE, there were challenges in reproducing genome-wide DNAm hits that are discussed.

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

Human disease is rarely a matter of all or nothing; variable expressivity is generally observed. Part of this variability is explained by somatic mosaicism, which can arise by a myriad of genetic alterations. These can take place at any stage of development, possibly leading to unusual features visible at birth, but can also occur later in life, conceivably leading to cancer. Previously, detection of somatic mosaicism was extremely challenging, as many gold standard tests lacked the necessary resolution. However, with the advances in high-throughput sequencing, mosaicism is being detected more frequently and at lower levels. This raises the issue of normal variation within each individual vs mosaicism leading to disease, and how to distinguish between the two. In this article, we will define somatic mosaicism with a brief overview of its main mechanisms in concrete clinical examples, discuss the impact of next-generation sequencing technologies in its detection, and expand on the clinical implications associated with a discovery of somatic mosaicism in the clinic.

The placenta is a multifunctional organ that regulates key aspects of pregnancy maintenance and fetal development. As the placenta is in direct contact with maternal blood, cellular products (DNA, RNA, proteins, etc.) from the placenta can enter maternal circulation by a variety of ways. The application of serum proteins and circulating placental derived DNA has been well demonstrated for the diagnosis of aneuploidy, and there is great interest in exploring the use of placental biomarkers for the prediction of a range of fetal health parameters. In this review, we discuss how placental biomarkers might be used for the diagnosis and early detection of preeclampsia, fetal growth restriction and inflammation associated with preterm birth. We emphasize how increased understanding of the underlying placental biology can aid in the interpretation of such approaches and development of new biomarkers that can help predict the onset of pregnancy and neonatal health concerns before they manifest.

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BackgroundPlacental 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.MethodsSamples 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.ResultsUsing 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.ConclusionsOur 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.Electronic supplementary materialThe online version of this article (10.1186/s13072-018-0234-9) contains supplementary material, which is available to authorized users.

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