Altered DNA methylation in human placenta after suspected preterm labour

Researcher: 
Schoorlemmer , Jon
Congress: 
International Federation of Placenta Associations 2017 Meeting (IFPA 2017)
Participation type: 
Póster
Other authors: 
Schoorlemmer J, Strunk M, Macías-Redondo S,Calvo P, Breton P,d Paules C, Oros D,
Year: 
2017
Location: 
Manchester, UK
Publication: 
Placenta 57 (2017) 225-335 Abstract P2.40.

OBJECTIVE:
Suspected preterm labour (SPL) occurs in around 9% of pregnancies. However, almost two-thirds of women admitted for threatened preterm labour ultimately deliver at term. Recent evidence suggests they may not be risk-free for fetal development. We analyzed whether threatened preterm labour per se is associated with altered placental epigenetic marker profiles. The main objective of our present study is to analyze methylation profiles in placental tissue from both term born (TB) and preterm (PT) born after suspected preterm labour. We selected candidate genes based on their altered methylation status in pregnancy-related pathologies.

METHODS:
We carried out a matched case-control study, comparing methylation levels in 58 CpG sites/ 7 genes in placental DNA in TPL (either TB or PT) and normal term births (n = 15 each), using sequencing of DNA amplified from bisulfite-treated DNA. We selected candidate genes based on published data showing altered methylation status in pregnancy-related pathologies.

RESULTS:
Placental samples from preterm and term deliveries after suspected preterm labour exhibited significantly increased methylation of 11B-HSD2, NR3C1 and CFB. Methylation was virtually absent from the VEGFA and FLT1 genes, and was not altered in SPL in the VEGFA, FLT1, TNFα and ZNF217 loci.

CONCLUSION:
Differential methylation in selected loci is associated with threatened preterm labour per se, and independent on term or preterm delivery. As a group they may serve as a potential biomarker or suggest an epigenetic mechanism altering gene transcription that contributes to TPL pathology. We are presently analyzing methylation data for additional loci, and try to relate methylation changes to gene expression levels.