Decreased Expression of Placental Proteins in Recurrent Pregnancy Loss: Functional Relevance and Diagnostic Value.

Miscarriages affect 50-70% of all conceptions and 15-20% of clinically recognized pregnancies. Recurrent pregnancy loss (RPL, ≥2 miscarriages) affects 1-5% of recognized pregnancies. Nevertheless, our knowledge about the etiologies and pathophysiology of RPL is incomplete, and thus, reliable diagnostic/preventive tools are not yet available. Here, we aimed to define the diagnostic value of three placental proteins for RPL: human chorionic gonadotropin free beta-subunit (free-ß-hCG), pregnancy-associated plasma protein-A (PAPP-A), and placental growth factor (PlGF). Blood samples were collected from women with RPL (n = 14) and controls undergoing elective termination of pregnancy (n = 30) at the time of surgery. Maternal serum protein concentrations were measured by BRAHMS KRYPTOR Analyzer. Daily multiple of median (dMoM) values were calculated for gestational age-specific normalization. To obtain classifiers, logistic regression analysis was performed, and ROC curves were calculated. There were differences in changes of maternal serum protein concentrations with advancing healthy gestation. Between 6 and 13 weeks, women with RPL had lower concentrations and dMoMs of free ß-hCG, PAPP-A, and PlGF than controls. PAPP-A dMoM had the best discriminative properties (AUC = 0.880). Between 9 and 13 weeks, discriminative properties of all protein dMoMs were excellent (free ß-hCG: AUC = 0.975; PAPP-A: AUC = 0.998; PlGF: AUC = 0.924). In conclusion, free-ß-hCG and PAPP-A are valuable biomarkers for RPL, especially between 9 and 13 weeks. Their decreased concentrations indicate the deterioration of placental functions, while lower PlGF levels indicate problems with placental angiogenesis after 9 weeks.

Exosomal small RNA profiling in first-trimester maternal blood explores early molecular pathways of preterm preeclampsia.

Introduction: Preeclampsia (PE) is a severe obstetrical syndrome characterized by new-onset hypertension and proteinuria and it is often associated with fetal intrauterine growth restriction (IUGR). PE leads to long-term health complications, so early diagnosis would be crucial for timely prevention. There are multiple etiologies and subtypes of PE, and this heterogeneity has hindered accurate identification in the presymptomatic phase. Recent investigations have pointed to the potential role of small regulatory RNAs in PE, and these species, which travel in extracellular vesicles (EVs) in the circulation, have raised the possibility of non-invasive diagnostics. The aim of this study was to investigate the behavior of exosomal regulatory small RNAs in the most severe subtype of PE with IUGR. Methods: We isolated exosomal EVs from first-trimester peripheral blood plasma samples of women who later developed preterm PE with IUGR (n=6) and gestational age-matched healthy controls (n=14). The small RNA content of EVs and their differential expression were determined by next-generation sequencing and further validated by quantitative real-time PCR. We also applied the rigorous exceRpt bioinformatics pipeline for small RNA identification, followed by target verification and Gene Ontology analysis. Results: Overall, >2700 small RNAs were identified in all samples and, of interest, the majority belonged to the RNA interference (RNAi) pathways. Among the RNAi species, 16 differentially expressed microRNAs were up-regulated in PE, whereas up-regulated and down-regulated members were equally found among the six identified Piwi-associated RNAs. Gene ontology analysis of the predicted small RNA targets showed enrichment of genes in pathways related to immune processes involved in decidualization, placentation and embryonic development, indicating that dysregulation of the induced small RNAs is connected to the impairment of immune pathways in preeclampsia development. Finally, the subsequent validation experiments revealed that the hsa_piR_016658 piRNA is a promising biomarker candidate for preterm PE associated with IUGR. Discussion: Our rigorously designed study in a homogeneous group of patients unraveled small RNAs in circulating maternal exosomes that act on physiological pathways dysregulated in preterm PE with IUGR. Therefore, our small RNA hits are not only suitable biomarker candidates, but the revealed biological pathways may further inform us about the complex pathology of this severe PE subtype.

Risk Estimation of Gestational Diabetes Mellitus in the First Trimester.

CONTEXT: There is no early, first-trimester risk estimation available to predict later (gestational week 24-28) gestational diabetes mellitus (GDM); however, it would be beneficial to start an early treatment to prevent the development of complications. OBJECTIVE: We aimed to identify early, first-trimester prediction markers for GDM. METHODS: The present case-control study is based on the study cohort of a Hungarian biobank containing biological samples and follow-up data from 2545 pregnant women. Oxidative-nitrative stress-related parameters, steroid hormone, and metabolite levels were measured in the serum/plasma samples collected at the end of the first trimester from 55 randomly selected control and 55 women who developed GDM later. RESULTS: Pregnant women who developed GDM later during the pregnancy were older and had higher body mass index. The following parameters showed higher concentration in their serum/plasma samples: fructosamine, total antioxidant capacity, testosterone, cortisone, 21-deoxycortisol; soluble urokinase plasminogen activator receptor, dehydroepiandrosterone sulfate, dihydrotestosterone, cortisol, and 11-deoxycorticosterone levels were lower. Analyzing these variables using a forward stepwise multivariate logistic regression model, we established a GDM prediction model with a specificity of 96.6% and sensitivity of 97.5% (included variables: fructosamine, cortisol, cortisone, 11-deoxycorticosterone, SuPAR). CONCLUSION: Based on these measurements, we accurately predict the development of later-onset GDM (24th-28th weeks of pregnancy). Early risk estimation provides the opportunity for targeted prevention and the timely treatment of GDM. Prevention and slowing the progression of GDM result in a lower lifelong metabolic risk for both mother and offspring.

Early pathways, biomarkers, and four distinct molecular subclasses of preeclampsia: The intersection of clinical, pathological, and high-dimensional biology studies.

Preeclampsia is a syndromic disease of the mother, fetus, and placenta. The main limitation in early and accurate diagnosis of preeclampsia is rooted in the heterogeneity of this syndrome as reflected by diverse molecular pathways, symptoms, and clinical outcomes. Gaps in our knowledge preclude successful early diagnosis, personalized treatment, and prevention. The advent of "omics" technologies and systems biology approaches addresses this problem by identifying the molecular pathways associated with the underlying mechanisms and clinical phenotypes of preeclampsia. Here, we provide a brief overview on how the field has progressed, focusing on studies utilizing state-of-the-art transcriptomics and proteomics methods. Moreover, we summarize our systems biology studies involving maternal blood proteomics and placental transcriptomics, which identified early maternal and placental disease pathways and showed that their interaction influences the clinical presentation of preeclampsia. We also present an analysis of maternal blood proteomics data which revealed distinct molecular subclasses of preeclampsia and their molecular mechanisms. Maternal and placental disease pathways behind these subclasses are similar to those recently reported in studies on the placental transcriptome. These findings may promote the development of novel diagnostic tools for the distinct subtypes of preeclampsia syndrome, enabling early detection and personalized follow-up and tailored care of patients.

Screening for preeclampsia in the first trimester of pregnancy in routine clinical practice in Hungary.

We aimed to evaluate the contribution of different factors in the Fetal Medicine Foundation algorithms for preeclampsia (PE) risk calculation during first-trimester screening in Hungary. We selected subjects for the nested case-control study from a prospective cohort of 2545 low-risk pregnancies. Eighty-two patients with PE and 82 gestational age-matched controls were included. Individual PE risk was calculated using two risk-assessing softwares. Using Astraia 2.3.1, considering maternal characteristics and biophysical parameters only, detection rates (DR) were 63.6% for early-PE and 67.6% for late-PE. When we added placenta associated plasma protein A (PAPP-A) to the risk calculation, DRs decreased to 54.5% and 64.8% respectively. Using Astraia 2.8.2 with maternal characteristics and biophysical parameters resulted in the DRs of 63.6% (early-PE) and 56.3% (late-PE). If we added PAPP-A to the risk calculation, DRs improved to 72.7% and 54.9%. The addition of placental growth factor (PlGF) did not increase detection rates in either calculation. In conclusion, using maternal characteristics, biophysical parameters, and PAPP-A, an acceptable screening efficacy could be achieved for early-PE during first-trimester screening. Since PlGF did not improve efficacy in our study, we suggest setting new standard curves for PlGF in Eastern European pregnant women, and the evaluation of novel biochemical markers.