TY - JOUR
T1 - Circulating transcripts in maternal blood reflect a molecular signature of early-onset preeclampsia
AU - Munchel, Sarah
AU - Rohrback, Suzanne
AU - Randise-Hinchliff, Carlo
AU - Kinnings, Sarah
AU - Deshmukh, Shweta
AU - Alla, Nagesh
AU - Tan, Catherine
AU - Kia, Amirali
AU - Greene, Grainger
AU - Leety, Linda
AU - Rhoa, Matthew
AU - Yeats, Scott
AU - Saul, Matthew
AU - Chou, Julia
AU - Bianco, Kimberley
AU - O'Shea, Kevin
AU - Bujold, Emmanuel
AU - Norwitz, Errol
AU - Wapner, Ronald
AU - Saade, George
AU - Kaper, Fiona
N1 - Publisher Copyright:
Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works
PY - 2020/7
Y1 - 2020/7
N2 - 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.
AB - 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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U2 - 10.1126/SCITRANSLMED.AAZ0131
DO - 10.1126/SCITRANSLMED.AAZ0131
M3 - Article
C2 - 32611681
AN - SCOPUS:85087473195
SN - 1946-6234
VL - 12
JO - Science Translational Medicine
JF - Science Translational Medicine
IS - 550
M1 - eaaz0131
ER -