Research ArticlePreeclampsia

Circulating transcripts in maternal blood reflect a molecular signature of early-onset preeclampsia

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Science Translational Medicine  01 Jul 2020:
Vol. 12, Issue 550, eaaz0131
DOI: 10.1126/scitranslmed.aaz0131

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Pinpointing preeclampsia

Preeclampsia is a poorly understood pregnancy-associated disorder. Often marked by hypertension, preeclampsia can lead to severe complications including internal bleeding, seizures, stroke, premature birth, and death. The condition can develop suddenly, and identifying who is at risk of preeclampsia is difficult. Munchel et al. examined circulating RNA in pregnant women who developed early-onset preeclampsia and found 49 transcripts of maternal, placental, and fetal origin that classified a small but independent cohort of pregnant women with early-onset preeclampsia. These transcripts may reveal preeclampsia biology and, if validated in a larger cohort, may enable much-needed preeclampsia diagnostics.

Abstract

Circulating RNA (C-RNA) is continually released into the bloodstream from tissues throughout the body, offering an opportunity to noninvasively monitor all aspects of pregnancy health from conception to birth. We asked whether C-RNA analysis could robustly detect aberrations in patients diagnosed with preeclampsia (PE), a prevalent and potentially fatal pregnancy complication. As an initial examination, we sequenced the circulating transcriptome from 40 pregnancies at the time of severe, early-onset PE diagnosis and 73 gestational age–matched controls. Differential expression analysis identified 30 transcripts with gene ontology annotations and tissue expression patterns consistent with the placental dysfunction, impaired fetal development, and maternal immune and cardiovascular system dysregulation characteristic of PE. Furthermore, machine learning identified combinations of 49 C-RNA transcripts that classified an independent cohort of patients (early-onset PE, n = 12; control, n = 12) with 85 to 89% accuracy. C-RNA may thus hold promise for improving the diagnosis and identification of at-risk pregnancies.

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