RNA profiles reveal signatures of future health and disease in pregnancy.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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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
Аннотация
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.