Abstract

Herein, we developed a specific, rapid sensor to quantify placental extracellular vesicle (EV) protein biomarkers of early pregnancy complications. A distinct tetraspanin CD9 and placental alkaline phosphatase (PLAP) expression pattern was observed via targeted multiple reaction monitoring of EVs from maternal plasma collected before 18 weeks of gestation. A classification model was developed using training and validation patient sets, distinguishing between individuals at high risk of developing complications from those with normal pregnancies, achieving 80% sensitivity, 90% specificity, 89% positive predictive value (PPV), and 82% negative predictive value (NPV). Superparamagnetic nanoflowers that captured target EVs (CD9(+)/PLAP(+)) were used to construct a 4-flex glass strip nanozymatic readout system. The sensor analyzes plasma for EVs, identifying gestational diabetes mellitus risk with a 95% combined sensitivity, 100% specificity, 100% PPV, and 96% NPV. This nanoplatform identifies individuals at risk of developing pregnancy complications with a >90% classification accuracy, exhibiting potential for clinical applications.