4.5 Article

Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes

期刊

EPIGENETICS
卷 16, 期 6, 页码 642-661

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/15592294.2020.1816774

关键词

Cell-free DNA; cell-free RNA; high-risk pregnancy; preeclampsia; gestational diabetes; gestational hypertension

资金

  1. National Institutes of Health (NIH) [R01HD089714, R01HD00015, U01HD087221]
  2. National Institutes of Health [R01HD089714, R01HD00015, U01HD087221]

向作者/读者索取更多资源

By analyzing the cell-free DNA and RNA content in maternal and cord blood plasma samples, researchers found that these substances may be used to predict adverse pregnancy outcomes early in gestation. They constructed a classifier with a high positive predictive ability for APOs, preeclampsia, and GDM.
Although analysis of maternal plasma cell-free content has been employed for screening of genetic abnormalities within a pregnancy, limited attention has been paid to its use for the detection of adverse pregnancy outcomes (APOs) based on placental function. Here we investigated cell-free DNA and RNA content of 102 maternal and 25 cord plasma samples. Employing a novel deconvolution methodology, we found that during the first trimester, placenta-specific DNA increased prior to the subsequent development of gestational diabetes with no change in patients with preeclampsia while decreasing with maternal obesity. Moreover, using cell-free RNA sequencing, APOs revealed 71 differentially expressed genes early in pregnancy. We noticed the upregulation of S100A8, MS4A3, and MMP8 that have been already associated with APOs but also the upregulation of BCL2L15 and the downregulation of ALPL that have never been associated with APOs. We constructed a classifier with a positive predictive ability (AUC) of 0.91 for APOs, 0.86 for preeclampsia alone and 0.64 for GDM. We conclude that placenta-specific cell-free nucleic acids during early gestation provide the possibility of predicting APOs prior to the emergence of characteristic clinical features.

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