Characterization of methylation profiles in spontaneous preterm birth placental villous tissue

Abstract

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.

Fig 1. Identification of methylation profiles using a comparative approach.

A. Differentially methylated positions were identified using pairwise comparisons in limma. Red points indicate significant DMPs with a threshold of log2 fold-change >1 and Benjamini Hochberg adjusted p-value <0.3. Blue lines represent log2 fold-change of 1. B. Genomic distribution of DMPs in the pairwise comparisons. The majority of DMPs in the isPTB and TB versus AHC comparisons are located inside or close to known CpG islands. However, in the isPTB versus TB comparison, the majority of DMPs are in open sea regions with no known islands within 4kb. C. The Venn diagram represents the intersection of pairwise comparisons to classify significant DMPs into isPTB and AHC specific methylation profiles.

Fig 2. Identification of significant methylation profiles for isPTB and AHC DMPs.

A. Three DMPs identified as having an isPTB specific methylation pattern where the isPTB samples were differentially methylated compared to the AHC or TB samples. The distribution of individual sample beta values was assessed to determine if there were outliers or artifacts influencing the methylation patterns. The dark bands represent the mean of the methylation values while the lighter grey bands represent the interquartile range. B. 6,177 DMPs demonstrating a methylation pattern where the AHC samples were differentially methylated compared to the isPTB or TB samples. The breakout heatmap shows the pattern or the top 25 more and less methylated samples and demonstrates the similarity of methylation between the isPTB and TB samples. The distribution of individual sample beta values was assessed to determine if there were outliers or artifacts influencing the methylation patterns.

Fig 3. isPTB specific DMR profile.

Differentially methylated DMRs were identified by differences in the mean of the probe values across the DMR. Only 7 isPTB DMRs had an isPTB specific profile where the isPTB DMRs were less methylated than the TB or AHC DMRs. Two of the DMRs overlap non-coding regions. No DMRs were identified that were more methylated.

Fig 4. AHC specific DMR profile.

A. Differentially methylated DMRs were identified by differences in the mean of the probe values across the DMR. AHC specific DMRs are defined by when the AHC DMRs were differentially methylated compared to the TB or isPTB DMRs. B. The top 25 more and less methylated DMRs demonstrates the clarity of the molecular profile, as there is no significant differential methylation in the TB vs isPTB comparison.