Circulating microparticle proteins predict pregnancies complicated by placenta accreta spectrum

被引:0
作者
Hope Y. Yu
Serena B. Gumusoglu
David E. Cantonwine
Daniela A. Carusi
Prem Gurnani
Brandon Schickling
Robert C. Doss
Mark K. Santillan
Kevin P. Rosenblatt
Thomas F. McElrath
机构
[1] Brigham and Women’s Hospital,Division of Maternal
[2] Harvard Medical School,Fetal Medicine, Department of Obstetrics and Gynecology
[3] University of Iowa Carver College of Medicine,Division of Oncology, Department of Internal Medicine
[4] NX Prenatal Inc.,undefined
[5] University of Texas Health Science Center at Houston,undefined
[6] McGovern Medical School,undefined
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Scientific Reports | / 12卷
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摘要
Placenta accreta spectrum (PAS) is characterized by abnormal attachment of the placenta to the uterus, and attempts at placental delivery can lead to catastrophic maternal hemorrhage and death. Multidisciplinary delivery planning can significantly improve outcomes; however, current diagnostics are lacking as approximately half of pregnancies with PAS are undiagnosed prior to delivery. This is a nested case–control study of 35 cases and 70 controls with the primary objective of identifying circulating microparticle (CMP) protein panels that identify pregnancies complicated by PAS. Size exclusion chromatography and liquid chromatography with tandem mass spectrometry were used for CMP protein isolation and identification, respectively. A two-step iterative workflow was used to establish putative panels. Using plasma sampled at a median of 26 weeks’ gestation, five CMP proteins distinguished PAS from controls with a mean area under the curve (AUC) of 0.83. For a separate sample taken at a median of 35 weeks’ gestation, the mean AUC was 0.78. In the second trimester, canonical pathway analyses demonstrate over-representation of processes related to iron homeostasis and erythropoietin signaling. In the third trimester, these analyses revealed abnormal immune function. CMP proteins classify PAS well prior to delivery and have potential to significantly reduce maternal morbidity and mortality.
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