Dataset Information

Locus-specific DNA methylation prediction in cord blood and placenta.

ABSTRACT: DNA methylation is known to be responsive to prenatal exposures, which may be a part of the mechanism linking early developmental exposures to future chronic diseases. Many studies use blood to measure DNA methylation, yet we know that DNA methylation is tissue specific. Placenta is central to fetal growth and development, but it is rarely feasible to collect this tissue in large epidemiological studies; on the other hand, cord blood samples are more accessible. In this study, based on paired samples of both placenta and cord blood tissues from 169 individuals, we investigated the methylation concordance between placenta and cord blood. We then employed a machine-learning-based model to predict locus-specific DNA methylation levels in placenta using DNA methylation levels in cord blood. We found that methylation correlation between placenta and cord blood is lower than other tissue pairs, consistent with existing observations that placenta methylation has a distinct pattern. Nonetheless, there are still a number of CpG sites showing robust association between the two tissues. We built prediction models for placenta methylation based on cord blood data and documented a subset of 1,012 CpG sites with high correlation between measured and predicted placenta methylation levels. The resulting list of CpG sites and prediction models could help to reveal the loci where internal or external influences may affect DNA methylation in both placenta and cord blood, and provide a reference data to predict the effects on placenta in future study even when the tissue is not available in an epidemiological study.

SUBMITTER: Ma B

PROVIDER: S-EPMC6557556 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Locus-specific DNA methylation prediction in cord blood and placenta.

Ma Baoshan B Allard Catherine C Bouchard Luigi L Perron Patrice P Mittleman Murray A MA Hivert Marie-France MF Liang Liming L

Epigenetics 20190318 4

DNA methylation is known to be responsive to prenatal exposures, which may be a part of the mechanism linking early developmental exposures to future chronic diseases. Many studies use blood to measure DNA methylation, yet we know that DNA methylation is tissue specific. Placenta is central to fetal growth and development, but it is rarely feasible to collect this tissue in large epidemiological studies; on the other hand, cord blood samples are more accessible. In this study, based on paired sa ...[more]

PMID: 30885044

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Project description:Exposure to phthalates has been shown to impede the human endocrine system, resulting in deleterious effects on pregnant women and their children. Phthalates modify DNA methylation patterns in infant cord blood. We examined the association between prenatal phthalate exposure and DNA methylation patterns in cord blood in a Korean birth cohort. Phthalate levels were measured in 274 maternal urine samples obtained during late pregnancy and 102 neonatal urine samples obtained at birth, and DNA methylation levels were measured in cord blood samples. For each infant in the cohort, associations between CpG methylation and both maternal and neonate phthalate levels were analyzed using linear mixed models. The results were combined with those from a meta-analysis of the levels of phthalates in maternal and neonatal urine samples, which were also analyzed for MEOHP, MEHHP, MnBP, and DEHP. This meta-analysis revealed significant associations between the methylation levels of CpG sites near the CHN2 and CUL3 genes, which were also associated with MEOHP and MnBP in neonatal urine. When the data were stratified by the sex of the infant, MnBP concentration was found to be associated with one CpG site near the OR2A2 and MEGF11 genes in female infants. In contrast, the concentrations of the three maternal phthalates showed no significant association with CpG site methylation. Furthermore, the data identified distinct differentially methylated regions in maternal and neonatal urine samples following exposure to phthalates. The CpGs with methylation levels that were positively associated with phthalate levels (particularly MEOHP and MnBP) were found to be enriched genes and related pathways. These results indicate that prenatal phthalate exposure is significantly associated with DNA methylation at multiple CpG sites. These alterations in DNA methylation may serve as biomarkers of maternal exposure to phthalates in infants and are potential candidates for investigating the mechanisms by which phthalates impact maternal and neonatal health.

Project description:BackgroundVariation in intercellular methylation patterns can complicate the use of methylation biomarkers for clinical diagnostic applications such as blood-based cancer testing. Here, we describe development and validation of a methylation density binary classification method called EpiClass (available for download at https://github.com/Elnitskilab/EpiClass ) that can be used to predict and optimize the performance of methylation biomarkers, particularly in challenging, heterogeneous samples such as liquid biopsies. This approach is based upon leveraging statistical differences in single-molecule sample methylation density distributions to identify ideal thresholds for sample classification.ResultsWe developed and tested the classifier using reduced representation bisulfite sequencing (RRBS) data derived from ovarian carcinoma tissue DNA and controls. We used these data to perform in silico simulations using methylation density profiles from individual epiallelic copies of ZNF154, a genomic locus known to be recurrently methylated in numerous cancer types. From these profiles, we predicted the performance of the classifier in liquid biopsies for the detection of epithelial ovarian carcinomas (EOC). In silico analysis indicated that EpiClass could be leveraged to better identify cancer-positive liquid biopsy samples by implementing precise thresholds with respect to methylation density profiles derived from circulating cell-free DNA (cfDNA) analysis. These predictions were confirmed experimentally using DREAMing to perform digital methylation density analysis on a cohort of low volume (1-ml) plasma samples obtained from 26 EOC-positive and 41 cancer-free women. EpiClass performance was then validated in an independent cohort of 24 plasma specimens, derived from a longitudinal study of 8 EOC-positive women, and 12 plasma specimens derived from 12 healthy women, respectively, attaining a sensitivity/specificity of 91.7%/100.0%. Direct comparison of CA-125 measurements with EpiClass demonstrated that EpiClass was able to better identify EOC-positive women than standard CA-125 assessment. Finally, we used independent whole genome bisulfite sequencing (WGBS) datasets to demonstrate that EpiClass can also identify other cancer types as well or better than alternative methylation-based classifiers.ConclusionsOur results indicate that assessment of intramolecular methylation density distributions calculated from cfDNA facilitates the use of methylation biomarkers for diagnostic applications. Furthermore, we demonstrated that EpiClass analysis of ZNF154 methylation was able to outperform CA-125 in the detection of etiologically diverse ovarian carcinomas, indicating broad utility of ZNF154 for use as a biomarker of ovarian cancer.

Project description:BackgroundGestational diabetes mellitus (GDM) is a common pregnancy-specific disease and is growing at an alarming rate worldwide, which can negatively affect the health of pregnant women and fetuses. However, most studies are limited to one tissue, placenta or umbilical cord blood, usually with one omics assay. It is thus difficult to systematically reveal the molecular mechanism of GDM and the key influencing factors on pregnant women and offspring.ResultsWe recruited a group of 21 pregnant women with GDM and 20 controls without GDM. For each pregnant woman, reduced representation bisulfite sequencing and RNA-seq were performed using the placenta and paired neonatal umbilical cord blood specimens. Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were identified with body mass index as a covariate. Through the comparison of GDM and control samples, 2779 and 141 DMRs, 1442 and 488 DEGs were identified from placenta and umbilical cord blood, respectively. Functional enrichment analysis showed that the placenta methylation and expression profiles of GDM women mirrored the molecular characteristics of "type II diabetes" and "insulin resistance." Methylation-altered genes in umbilical cord blood were associated with pathways "type II diabetes" and "cholesterol metabolism." Remarkably, both DMRs and DEGs illustrated significant overlaps among placenta and umbilical cord blood samples. The overlapping DMRs were associated with "cholesterol metabolism." The top-ranking pathways enriched in the shared DEGs include "growth hormone synthesis, secretion and action" and "type II diabetes mellitus."ConclusionsOur research demonstrated the epigenetic and transcriptomic alternations of GDM women and offspring. Our findings emphasized the importance of epigenetic modifications in the communication between pregnant women with GDM and offspring, and provided a reference for the prevention, control, treatment, and intervention of perinatal deleterious events of GDM and neonatal complications.

Dataset Information

Locus-specific DNA methylation prediction in cord blood and placenta.

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Locus-specific DNA methylation prediction in cord blood and placenta.

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