Proteomic signatures predict preeclampsia in individual cohorts but not across cohorts – implications for clinical biomarker studies

Mohammad S. Ghaemi, Adi L. Tarca, Roberto Romero, Natalie Stanley, Ramin Fallahzadeh, Athena Tanada, Anthony Culos, Kazuo Ando, Xiaoyuan Han, Yair J. Blumenfeld, Maurice L. Druzin, Yasser Y. El-Sayed, Ronald S. Gibbs, Virginia D. Winn, Kevin Contrepois, Xuefeng B. Ling, Ronald J. Wong, Gary M. Shaw, David K. Stevenson, Brice Gaudilliere, Nima Aghaeepour & Martin S. Angst
Early identification of pregnant women at risk for preeclampsia (PE) is important, as it will enable targeted interventions ahead of clinical manifestations. The quantitative analyses of plasma proteins feature prominently among molecular approaches used for risk prediction. However, derivation of protein signatures of sufficient predictive power has been challenging. The recent availability of platforms simultaneously assessing over 1000 plasma proteins offers broad examinations of the plasma proteome, which may enable the extraction of proteomic signatures...
1 citation reported since publication in 2021.
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