Placental DNA may predict pregnancy complications

New research suggests that placental DNA may have potential as a biomarker for adverse pregnancy outcomes (APOs).

The first-of-its-kind analysis, done in a small sample of pregnant patients, shows that placenta-specific DNA increases prior to clinical development of gestational diabetes and that cell-free RNA (cfRNA) has a high positive predictive ability in detection of APOs.

Published in Epigenetics,1 the results are from a study funded by the National Institute of Child Health and Human Development’s Human Placenta Project, a collaborative effort aimed at understanding the role of the placenta in health and disease. The study of cell-free DNA (cfDNA) methylation and transcriptomic signature prediction was led by researchers from UCLA.

For the analysis, the authors applied a method developed to deconvolute trace amounts of tumor DNA from the plasma background and extended it to extremely low-coverage sequencing data.

They used the method, along with RNA sequencing, to test the hypothesis that cfDNA and cfRNA in maternal circulation may correlate with placental health and could be employed to differentiate between gestational disorders and normal, complication-free gestation.

Related: DNA sequencing technique may help prenatally detect NIHF

The participants were women in their first trimester from February 2017 to 2019 who were enrolled in the PARENTS prospective cohort study, which is looking at mechanisms for and prediction of APOs. Of the 160 subjects in that study who have delivered, 61 had APOs.

The present placenta-specific DNA research included nine women with normal pregnancies, five with preeclampsia, three with gestational hypertension, and seven with gestational diabetes mellitus (GDM).

GDM was defined as any degree of glucose intolerance initially recognized in pregnancy. Preeclampsia was defined as blood pressure ≥140/90 on two occasions at least 4 hours apart after 20 weeks’ gestation with a previously normal blood pressure and proteinuria of 300 mg for ≥24 hours.

Five different samples were taken from each subject at time points from 12 to 17 weeks, 18 to 22 weeks, 35 to 37 weeks, at delivery, and from cord blood. Plasma was also collected from seven women who served as controls.

The authors found that the placental fraction in GDM significantly increased compared with normal pregnancies in the first trimester and the trend persisted through the second and third trimesters, although it was not statistically significant.

Early detection of a difference between pregnancies with GDM (mean 7.2%) and that were normal (mean 4%) based on the placental fraction, the researchers said, is of interest for future development of predictive biomarkers.

Non-placental tissue-of-origin, namely pancreatic cfDNA fraction, also was significantly increased only in the first trimester in subjects who went on to develop GDM. Pancreatic cfDNA also increased in the GDM cord blood, perhaps signaling future pancreatic dysregulation in the offspring.

The authors used cfRNA sequencing information from the first trimester to identify candidate biomarkers for detection of likelihood of developing APOs.

A logistic regression model showed that upregulation of the genes S100A8, MS4A3, and MMP8 was associated with APOs as were upregulation of BCL2L15 and downregulation of ALPL. The classifier had a positive predictive value of 0.91 for APOs, 0.86 for preeclampsia alone, and 0.64 for GDM.

Taking these results together, the researchers “presented cfDNA methylation signatures and transcriptomic signatures early in gestation that collectively could potentially assist in the prediction of subsequent development of APOs, prior to emergence of characteristic clinical features.”

Their findings, the authors said, point to a need for a larger multicenter clinical trial and suggest that “these non-invasive approaches may be used effectively early in gestation.”



  1. Del Vecchio G, Li Q, Li W, et al. Cell-free DNA methylation and transcriptomic signature prediction of pregnancies with adverse outcomes. Epigenetics. Published online: 13 Oct 2020 doi: 10.1080/15592294.2020.1816774
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