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RNA profiles reveal signatures of future health and disease in pregnancy

Authors :
Rasmussen, Morten
Reddy, Mitsu
Nolan, Rory
Camunas-Soler, Joan
Khodursky, Arkady
Scheller, Nikolai M.
Cantonwine, David E.
Engelbrechtsen, Line
Mi, Jia Dai
Dutta, Arup
Brundage, Tiffany
Siddiqui, Farooq
Thao, Mainou
Gee, Elaine P. S.
La, Johnny
Baruch-Gravett, Courtney
Santillan, Mark K.
Deb, Saikat
Ame, Shaali M.
Ali, Said M.
Adkins, Melanie
DePristo, Mark A.
Lee, Manfred
Namsaraev, Eugeni
Gybel-Brask, Dorte Jensen
Skibsted, Lillian
Litch, James A.
Santillan, Donna A.
Sazawal, Sunil
Tribe, Rachel M.
Roberts, James M.
Jain, Maneesh
Høgdall, Estrid
Holzman, Claudia
Quake, Stephen R.
Elovitz, Michal A.
McElrath, Thomas F.
Source :
Nature; January 2022, Vol. 601 Issue: 7893 p422-427, 6p
Publication Year :
2022

Abstract

Maternal morbidity and mortality continue to rise, and pre-eclampsia is a major driver of this burden1. Yet the ability to assess underlying pathophysiology before clinical presentation to enable identification of pregnancies at risk remains elusive. Here we demonstrate the ability of plasma cell-free RNA (cfRNA) to reveal patterns of normal pregnancy progression and determine the risk of developing pre-eclampsia months before clinical presentation. Our results centre on comprehensive transcriptome data from eight independent prospectively collected cohorts comprising 1,840 racially diverse pregnancies and retrospective analysis of 2,539 banked plasma samples. The pre-eclampsia data include 524 samples (72 cases and 452 non-cases) from two diverse independent cohorts collected 14.5 weeks (s.d., 4.5 weeks) before delivery. We show that cfRNA signatures from a single blood draw can track pregnancy progression at the placental, maternal and fetal levels and can robustly predict pre-eclampsia, with a sensitivity of 75% and a positive predictive value of 32.3% (s.d., 3%), which is superior to the state-of-the-art method2. cfRNA signatures of normal pregnancy progression and pre-eclampsia are independent of clinical factors, such as maternal age, body mass index and race, which cumulatively account for less than 1% of model variance. Further, the cfRNA signature for pre-eclampsia contains gene features linked to biological processes implicated in the underlying pathophysiology of pre-eclampsia.

Details

Language :
English
ISSN :
00280836 and 14764687
Volume :
601
Issue :
7893
Database :
Supplemental Index
Journal :
Nature
Publication Type :
Periodical
Accession number :
ejs58642057
Full Text :
https://doi.org/10.1038/s41586-021-04249-w