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Objective: Placental growth factor testing decreases time to recognition of preeclampsia and may reduce severe maternal adverse outcomes. This analysis aims to describe the clinical phenotype of women by PlGF concentration, and to determine the mechanism(s) underpinning the reduction in severe maternal adverse outcomes in the PARROT trial, in order to inform how PlGF testing may be optimally used within clinical management algorithms., Study Design: This was a planned secondary analysis from the PARROT trial that compared revealed PlGF testing and management guidance with usual care in the assessment of women with suspected preterm preeclampsia., Main Outcome Measures: Maternal and perinatal outcomes following stratification of women by trial group, and measured PlGF concentration., Results: 1006 women were included. PlGF < 100 pg/ml identified women with more marked hypertension, increased adverse maternal outcomes and preterm delivery rates, and higher rates of small for gestational age infants. There was a reduction in adverse maternal outcomes in women whose results were revealed when PlGF levels were 12-100 pg/ml compared to usual care (3.8% vs 6.9%; aOR 0.15(95% CI 0.03-0.92). There was no significant difference in gestation at delivery between concealed or revealed groups in any PlGF categories., Conclusion: Low PlGF concentrations are associated with severe preeclampsia. The reduction in severe adverse maternal outcomes may be mediated through quicker diagnosis and intensive surveillance, as recommended by the management algorithm for those at increased risk. PlGF is particularly beneficial in those who test 12-100 pg/ml, as these may be women with silent multi-organ disease who otherwise may go undetected., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Preeclampsia remains a leading cause of maternal and perinatal morbidity and mortality. Accurate prediction of preeclampsia risk would enable more effective, risk-based prenatal care pathways. Current risk assessment algorithms depend on clinical risk factors largely unavailable for first-time pregnant women. Delivering accurate preeclampsia risk assessment to this cohort of women, therefore requires for novel biomarkers. Here, we evaluated the relevance of metabolite biomarker candidates for their selection into a prototype rapid, quantitative Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS) based clinical screening assay. First, a library of targeted LC-MS/MS assays for metabolite biomarker candidates was developed, using a medium-throughput translational metabolomics workflow, to verify biomarker potential in the Screening-for-Pregnancy-Endpoints (SCOPE, European branch) study. A variable pre-selection step was followed by the development of multivariable prediction models for pre-defined clinical use cases, i.e., prediction of preterm preeclampsia risk and of any preeclampsia risk. Within a large set of metabolite biomarker candidates, we confirmed the potential of dilinoleoyl-glycerol and heptadecanoyl-2-hydroxy-sn-glycero-3-phosphocholine to effectively complement Placental Growth Factor, an established preeclampsia biomarker, for the prediction of preeclampsia risk in first-time pregnancies without overt risk factors. These metabolites will be considered for integration in a prototype rapid, quantitative LC-MS/MS assay, and subsequent validation in an independent cohort., Competing Interests: Leslie W. Brown and Robin Tuytten are employees of Metabolomic Diagnostics. Alison E Bond was an employee of Metabolomic Diagnostics at the time this work was conducted. Grégoire Thomas is the owner of SQU4RE, an independent Statistics and Data mining provider. This does not alter our adherence to PLOS ONE policies on sharing data and materials. Louise C. Kenny and Philip N. Baker are minority shareholders of Metabolomic Diagnostics. Leslie W. Brown, Robin Tuytten, Grégoire Thomas and Louise C. Kenny are named inventors on a Patent Application which discloses the use of specific proteins and metabolites to predict preeclampsia risk, and which is assigned to Metabolomic Diagnostics, i.e., “Methods of predicting pre term birth from preeclampsia using metabolic and protein biomarkers”, with publication number WO2019155075A1. This does not alter our adherence to PLOS ONE policies on sharing data and materials. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Preeclampsia is a serious complication of pregnancy, affecting both maternal and fetal health. In genome-wide association meta-analysis of European and Central Asian mothers, we identify sequence variants that associate with preeclampsia in the maternal genome at ZNF831/20q13 and FTO/16q12. These are previously established variants for blood pressure (BP) and the FTO variant has also been associated with body mass index (BMI). Further analysis of BP variants establishes that variants at MECOM/3q26, FGF5/4q21 and SH2B3/12q24 also associate with preeclampsia through the maternal genome. We further show that a polygenic risk score for hypertension associates with preeclampsia. However, comparison with gestational hypertension indicates that additional factors modify the risk of preeclampsia.

Preeclampsia, which affects approximately 5% of pregnancies, is a leading cause of maternal and perinatal death. The causes of preeclampsia remain unclear, but there is evidence for inherited susceptibility. Genome-wide association studies (GWAS) have not identified maternal sequence variants of genome-wide significance that replicate in independent data sets. We report the first GWAS of offspring from preeclamptic pregnancies and discovery of the first genome-wide significant susceptibility locus (rs4769613; P = 5.4 × 10 -11 ) in 4,380 cases and 310,238 controls. This locus is near the FLT1 gene encoding Fms-like tyrosine kinase 1, providing biological support, as a placental isoform of this protein (sFlt-1) is implicated in the pathology of preeclampsia. The association was strongest in offspring from pregnancies in which preeclampsia developed during late gestation and offspring birth weights exceeded the tenth centile. An additional nearby variant, rs12050029, associated with preeclampsia independently of rs4769613. The newly discovered locus may enhance understanding of the pathophysiology of preeclampsia and its subtypes.

An overrepresentation of adverse pregnancy outcomes has been observed in pregnancies associated with a male fetus. We investigated the association between fetal gender and candidate biomarkers for preeclampsia. Proteins were quantified in samples taken at 20 weeks from women recruited to the SCreening fOr Pregnancy Endpoints (SCOPE) study (preeclampsia n = 150; no preeclampsia n = 450). In contrast to placental growth factor, soluble endoglin, and insulin-like growth factor acid labile subunit, levels of metallopeptidase domain 12 (ADAM12) at 20 weeks were dependent on fetal gender in pregnancies complicated by preeclampsia, for male (n = 73) fetuses the multiples of the median (MoM; interquartile range [IQR] 1.1-1.5) was 1.3, whereas for female fetuses (n = 75) MoM was 1.1 (1.0-1.3); P < .01. Prediction of preeclampsia using ADAM12 levels was improved for pregnancies associated with a male fetus (area under receiver-operator curve [AUC] 0.73 [95% confidence interval [CI] 0.67-0.80]) than that of a female fetus (AUC 0.62 [0.55-0.70]); P = .03. The data presented here fit a contemporary hypothesis that there is a difference between the genders in response to an adverse maternal environment and suggest that an alteration in ADAM12 may reflect an altered placental response in pregnancies subsequently complicated by preeclampsia., (© The Author(s) 2014.)

More than half of all cases of preeclampsia occur in healthy first-time pregnant women. Our aim was to develop a method to predict those at risk by combining clinical factors and measurements of biomarkers in women recruited to the Screening for Pregnancy Endpoints (SCOPE) study of low-risk nulliparous women. Forty-seven biomarkers identified on the basis of (1) association with preeclampsia, (2) a biological role in placentation, or (3) a role in cellular mechanisms involved in the pathogenesis of preeclampsia were measured in plasma sampled at 14 to 16 weeks' gestation from 5623 women. The cohort was randomly divided into training (n=3747) and validation (n=1876) cohorts. Preeclampsia developed in 278 (4.9%) women, of whom 28 (0.5%) developed early-onset preeclampsia. The final model for the prediction of preeclampsia included placental growth factor, mean arterial pressure, and body mass index at 14 to 16 weeks' gestation, the consumption of ≥3 pieces of fruit per day, and mean uterine artery resistance index. The area under the receiver operator curve (95% confidence interval) for this model in training and validation cohorts was 0.73 (0.70-0.77) and 0.68 (0.63-0.74), respectively. A predictive model of early-onset preeclampsia included angiogenin/placental growth factor as a ratio, mean arterial pressure, any pregnancy loss <10 weeks, and mean uterine artery resistance index (area under the receiver operator curve [95% confidence interval] in training and validation cohorts, 0.89 [0.78-1.0] and 0.78 [0.58-0.99], respectively). Neither model included pregnancy-associated plasma protein A, previously reported to predict preeclampsia in populations of mixed parity and risk. In nulliparous women, combining multiple biomarkers and clinical data provided modest prediction of preeclampsia., (© 2014 American Heart Association, Inc.)

Preeclampsia, a hypertensive pregnancy complication, is largely unpredictable in healthy nulliparous pregnant women. Accurate preeclampsia prediction in this population would transform antenatal care. To identify novel protein markers relevant to the prediction of preeclampsia, a 3-step mass spectrometric work flow was applied. On selection of candidate biomarkers, mostly from an unbiased discovery experiment (19 women), targeted quantitation was used to verify and validate candidate biomarkers in 2 independent cohorts from the SCOPE (SCreening fOr Pregnancy Endpoints) study. Candidate proteins were measured in plasma specimens collected at 19 to 21 weeks' gestation from 100 women who later developed preeclampsia and 200 women without preeclampsia recruited from Australia and New Zealand. Protein levels (n=25), age, and blood pressure were then analyzed using logistic regression to identify multimarker models (maximum 6 markers) that met predefined criteria: sensitivity ≥50% at 20% positive predictive value. These 44 algorithms were then tested in an independent European cohort (n=300) yielding 8 validated models. These 8 models detected 50% to 56% of preeclampsia cases in the training and validation sets; the detection rate for preterm preeclampsia cases was 80%. Validated models combine insulin-like growth factor acid labile subunit and soluble endoglin, supplemented with maximally 4 markers of placental growth factor, serine peptidase inhibitor Kunitz type 1, melanoma cell adhesion molecule, selenoprotein P, and blood pressure. Predictive performances were maintained when exchanging mass spectrometry measurements with ELISA measurements for insulin-like growth factor acid labile subunit. In conclusion, we demonstrated that biomarker combinations centered on insulin-like growth factor acid labile subunit have the potential to predict preeclampsia in healthy nulliparous women.

Using (1)H-nuclear magnetic resonance (NMR) spectroscopy and statistical models, we sought to identify ''biomarkers'' present in erythrocytes that would distinguish between women with normal pregnancy and those suffering from preeclampsia, and investigate possible links with previously identified plasma ''markers.'' Erythrocytes from 22 normotensive pregnant women and 15 preeclamptics were analyzed by (1)H Carr-Purcell-Meiboom-Gill (CPMG) NMR. Multivariate analysis and logistic regression were applied to differentiate between the 2 groups of patients, and used to develop a diagnostic model based on the concentrations of the constituents identified as being influential. Significantly higher concentrations of alanine (P < .001), glycine (P = .025), and ergothioneine (P = .049) were found in erythrocytes from preeclamptic patients. Discriminant analysis and regression of NMR data permitted 100% accurate diagnosis of the health status of new patients. Chemically related imidazole-based molecules, histidine and ergothioneine, are important in the classification process and the etiology of preeclampsia (PE).

Objectives: There is conflicting literature regarding the correlation between aromatic amino acid concentrations and the occurrence of preeclampsia (PE). The object of this study was to test whether these molecules could enable discrimination between healthy and preeclamptic pregnancies when detected using (1)H nuclear magnetic resonance spectroscopy., Methods: Plasma samples from 11 normotensive and 11 preeclamptic pregnant women were analyzed using (1)H-NMR. The the aromatic region of the spectrum was divided into regions of uniform size. The area of each region was subjected to principal component analysis., Results: A distinction was made between normal and preeclamptic pregnancies on the basis of histidine, tyrosine, and phenylalanine concentrations. The concentration of histidine was significantly higher in the plasma of patients with PE than in that of normotensive women (p = 0.003)., Conclusion: (1)H-NMR-based analysis of biofluids is capable of differentiating between patients with and without preeclampsia.

Objective: Using (1)H-nuclear magnetic resonance spectroscopy and chemometrics, we sought to establish the metabolic profile for preeclampsia and to identify biomarkers that would permit a distinction between women with a normal pregnancy and those suffering from preeclampsia., Methods: Plasma samples from 11 normotensive pregnant women and 11 women with preeclampsia were analyzed. Principal component analysis was applied to differentiate between the two groups of patients., Results: Lipid concentrations were found to be significantly lower in the plasma of patients suffering from preeclampsia than those in normotensive pregnant women (p = 0.031). There is also evidence to suggest that ketone body constituents may contribute to the discrimination., Conclusion: (1)H-nuclear magnetic resonance-based metabolic profiling can detect patients with preeclampsia.