TY - JOUR AU - Tarca, Adi L AU - Romero, Roberto AU - Benshalom-Tirosh, Neta AU - Than, Nándor Gábor AU - Gudicha, Dereje W AU - Done, Bogdan AU - Pacora, Percy AU - Chaiworapongsa, Tinnakorn AU - Panaitescu, Bogdan AU - Tirosh, Dan AU - Gomez-Lopez, Nardhy AU - Draghici, Sorin AU - Hassan, Sonia S AU - Erez, Offer TI - The prediction of early preeclampsia: Results from a longitudinal proteomics study. Results from a longitudinal proteomics study. TS - Results from a longitudinal proteomics study. JF - PLOS ONE J2 - PLOS ONE VL - 14 PY - 2019 IS - 6 PG - 34 SN - 1932-6203 DO - 10.1371/journal.pone.0217273 UR - https://m2.mtmt.hu/api/publication/30706654 ID - 30706654 AB - To identify maternal plasma protein markers for early preeclampsia (delivery <34 weeks of gestation) and to determine whether the prediction performance is affected by disease severity and presence of placental lesions consistent with maternal vascular malperfusion (MVM) among cases.This longitudinal case-control study included 90 patients with a normal pregnancy and 33 patients with early preeclampsia. Two to six maternal plasma samples were collected throughout gestation from each woman. The abundance of 1,125 proteins was measured using high-affinity aptamer-based proteomic assays, and data were modeled using linear mixed-effects models. After data transformation into multiples of the mean values for gestational age, parsimonious linear discriminant analysis risk models were fit for each gestational-age interval (8-16, 16.1-22, 22.1-28, 28.1-32 weeks). Proteomic profiles of early preeclampsia cases were also compared to those of a combined set of controls and late preeclampsia cases (n = 76) reported previously. Prediction performance was estimated via bootstrap.We found that 1) multi-protein models at 16.1-22 weeks of gestation predicted early preeclampsia with a sensitivity of 71% at a false-positive rate (FPR) of 10%. High abundance of matrix metalloproteinase-7 and glycoprotein IIbIIIa complex were the most reliable predictors at this gestational age; 2) at 22.1-28 weeks of gestation, lower abundance of placental growth factor (PlGF) and vascular endothelial growth factor A, isoform 121 (VEGF-121), as well as elevated sialic acid binding immunoglobulin-like lectin 6 (siglec-6) and activin-A, were the best predictors of the subsequent development of early preeclampsia (81% sensitivity, FPR = 10%); 3) at 28.1-32 weeks of gestation, the sensitivity of multi-protein models was 85% (FPR = 10%) with the best predictors being activated leukocyte cell adhesion molecule, siglec-6, and VEGF-121; 4) the increase in siglec-6, activin-A, and VEGF-121 at 22.1-28 weeks of gestation differentiated women who subsequently developed early preeclampsia from those who had a normal pregnancy or developed late preeclampsia (sensitivity 77%, FPR = 10%); 5) the sensitivity of risk models was higher for early preeclampsia with placental MVM lesions than for the entire early preeclampsia group (90% versus 71% at 16.1-22 weeks; 87% versus 81% at 22.1-28 weeks; and 90% versus 85% at 28.1-32 weeks, all FPR = 10%); and 6) the sensitivity of prediction models was higher for severe early preeclampsia than for the entire early preeclampsia group (84% versus 71% at 16.1-22 weeks).We have presented herein a catalogue of proteome changes in maternal plasma proteome that precede the diagnosis of preeclampsia and can distinguish among early and late phenotypes. The sensitivity of maternal plasma protein models for early preeclampsia is higher in women with underlying vascular placental disease and in those with a severe phenotype. LA - English DB - MTMT ER - TY - JOUR AU - Biró, Orsolya AU - Nagy, Bálint AU - Rigó, János TI - Identifying miRNA regulatory mechanisms in preeclampsia by systems biology approaches JF - HYPERTENSION IN PREGNANCY J2 - HYPERT PREGN VL - 36 PY - 2017 IS - 1 SP - 90 EP - 99 PG - 10 SN - 1064-1955 DO - 10.1080/10641955.2016.1239736 UR - https://m2.mtmt.hu/api/publication/3152197 ID - 3152197 AB - BACKGROUND: Preeclampsia (PE) is the major cause of maternal and fetal morbidity and mortality, affecting 3-8% of all pregnancies around the globe. miRNAs are small, noncoding RNA molecules, which negatively regulate gene expression. Abnormally expressed miRNAs contribute to pregnancy complications such as PE. The aim of our study was to find possible regulatory mechanisms by system biology approaches, which are connected to the pathogenesis of PE. METHODS: We integrated publicly available miRNA and gene expression profiles and created a network from the significant miRNA-mRNA pairs with the help of MAGIA and Cytoscape softwares. Two subnetworks were expanded by adding protein-protein interactions. Differentially expressed miRNAs were identified for the evaluation of their regulatory effect. We analyzed the miRNAs and their targets using different bioinformatics tools and through literature research. RESULTS: Altogether, 52,603 miRNA-mRNA interactions were generated by the MAGIA web tool. The top 250 interactions were visualized and pairs with q < 0.0001 were analyzed, which included 85 nodes and 80 edges signalizing the connections between 52 regulated genes and 33 miRNAs. A total of 11 of the regulated genes are PE related and 9 of them were targeted by multiple miRNAs. A total of 8 miRNAs were associated with PE before, and 13 miRNAs regulated more than 1 mRNA. Hsa-mir-210 was the highest degree node in the network and its role in PE is well established. CONCLUSIONS: We identified several miRNA-mRNA regulatory mechanisms which may contribute to the pathogenesis of PE. Further investigations are needed to validate these miRNA-mRNA interactions and to enlighten the possibilities of developing potential therapeutic targets. LA - English DB - MTMT ER -