A novel multiple marker microarray analyzer and methodology to predict major obstetric syndromes using surface markers of circulating extracellular vesicles from maternal plasma - Malene Møller Jørgensen; Rikke Bæk; Jenni K. Sloth; Rami Sammour; Adi Sharabi‐Nov; Manu Vatish; Hamutal Meiri; Marei Sammar (Acta Obstetricia et Gynecologica Scandinavica)
Abstract Introduction Placental‐derived extracellular vesicles (EVs) are nano‐organelles that facilitate intercellular communication between the feto‐placental unit and the mother. We evaluated a novel Multiple Microarray analyzer for identifying surface markers on plasma EVs that predict preterm delivery and preeclampsia compared to term delivery controls. Material and Methods In this prospective exploratory cohort study pregnant women between 24 and 40 gestational weeks with preterm delivery (n = 16), preeclampsia (n = 19), and matched term delivery controls (n = 15) were recruited from Bnai Zion Medical Center, Haifa, Israel. Plasma samples were tested using a multiple microarray analyzer. Glass slides with 17 antibodies against EV surface receptors ‐ were incubated with raw plasma samples, detected by biotinylated secondary antibodies specific to EVs or placental EVs (PEVs), and labeled with cyanine 5–streptavidin. PBS and whole human IgG served as controls. The fluorescent signal ratio to negative controls was log 2 transformed and analyzed for sensitivity and specificity using the area under the receiver operating characteristics curves (AUROC). Best pair ratios of general EVs/PEVs were used for univariate analysis, and top pairs were combined for multivariate analysis. Results were validated by comparison with EVs purified using standard procedures. Results Heatmaps differentiated surface profiles of preeclampsia, preterm delivery, and term delivery receptors on total EVs and PEVs. Similar results were obtained with enriched EVs and EVs from raw plasma. Univariate analyses identified markers predicting preterm delivery and preeclampsia over term delivery controls with AUC >0.6 and sensitivity >50% at 80% specificity. Combining the best markers in a multivariate model, preeclampsia prediction over term delivery had an AUC of 0.89 (95% CI: 0.72–1.0) with 90% sensitivity and 90% specificity, marked by inflammation (TNF RII), relaxation (placenta protein 13 (PP13)), and immune‐modulation (LFA1) receptors. Preterm delivery prediction over term delivery had an AUC of 0.97 (0.94–1.0), 84% sensitivity, and 90% specificity, marked by cell adhesion (ICAM), immune suppression, and general EV markers (CD81, CD82, and Alix). Preeclampsia prediction over preterm delivery had an AUC of 0.91 (0.79–0.99) with 80% sensitivity and 90% specificity with markers for complement activation (C1q) and autoimmunity markers. Conclusions The new, robust EV Multi‐Array analyzer and methodology offer a simple, fast diagnostic tool that reveals novel surface markers for major obstetric syndromes.