Jenny Myers

Diagnostic Accuracy of Placental Growth Factor in Women With Suspected Preeclampsia A Prospective Multicenter Study

Background— Hypertensive disorders of pregnancy are a major contributor to death and disability for pregnant women and their infants. The diagnosis of preeclampsia by using blood pressure and proteinuria is of limited use because they are tertiary, downstream features of the disease. Placental growth factor (PlGF) is an angiogenic factor, a secondary marker of associated placental dysfunction in preeclampsia, with known low plasma concentrations in the disease. Methods and Results— In a prospective multicenter study, we studied the diagnostic accuracy of low plasma PlGF concentration (<5th centile for gestation, Alere Triage assay) in women presenting with suspected preeclampsia between 20 and 35 weeks’ gestation (and up to 41 weeks’ gestation as a secondary analysis). The outcome was delivery for confirmed preeclampsia within 14 days. Of 625 women, 346 (55%) developed confirmed preeclampsia. In 287 women enrolled before 35 weeks’ gestation, PlGF <5th centile had high sensitivity (0.96; 95% confidence interval, 0.89–0.99) and negative predictive value (0.98; 0.93–0.995) for preeclampsia within 14 days; specificity was lower (0.55; 0.48–0.61). Area under the receiver operating characteristic curve for low PlGF (0.87, standard error 0.03) for predicting preeclampsia within 14 days was greater than all other commonly used tests, singly or in combination (range, 0.58–0.76), in women presenting with suspected preeclampsia (P<0.001 for all comparisons). Conclusions— In women presenting before 35 weeks’ gestation with suspected preeclampsia, low PlGF has high sensitivity and negative predictive value for preeclampsia within 14 days, is better than other currently used tests, and presents an innovative adjunct to management of such women.

Early pregnancy prediction of preeclampsia in nulliparous women, combining clinical risk and biomarkers: the Screening for Pregnancy Endpoints (SCOPE) international cohort study

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. # Novelty and Significance {#article-title-41}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.

Novel biomarkers for pre-eclampsia detected using metabolomics and machine learning

Pre-eclampsia is a multi-system disorder of pregnancy with major maternal and perinatal implications. Emerging therapeutic strategies are most likely to be maximally effective if commenced weeks or even months prior to the clinical presentation of the disease. Although widespread plasma alterations precede the clinical onset of pre-eclampsia, no single plasma constituent has emerged as a sensitive or specific predictor of risk. Consequently, currently available methods of identifying the condition prior to clinical presentation are of limited clinical use. We have exploited genetic programming, a powerful data mining method, to identify patterns of metabolites that distinguish plasma from patients with pre-eclampsia from that taken from healthy, matched controls. High-resolution gas chromatography time-of-flight mass spectrometry (GC-tof-MS) was performed on 87 plasma samples from women with pre-eclampsia and 87 matched controls. Normalised peak intensity data were fed into the Genetic Programming (GP) system which was set up to produce a model that gave an output of 1 for patients and 0 for controls. The model was trained on 50% of the data generated and tested on a separate hold-out set of 50%. The model generated by GP from the GC-tof-MS data identified a metabolomic pattern that could be used to produce two simple rules that together discriminate pre-eclampsia from normal pregnant controls using just 3 of the metabolite peak variables, with a sensitivity of 100% and a specificity of 98%. Thus, pre-eclampsia can be diagnosed at the level of small-molecule metabolism in blood plasma. These findings justify a prospective assessment of metabolomic technology as a screening tool for pre-eclampsia, while identification of the metabolites involved may lead to an improved understanding of the aetiological basis of pre-eclampsia and thus the development of targeted therapies.

Angiogenic factors combined with clinical risk factors to predict preterm pre-eclampsia in nulliparous women: a predictive test accuracy study.

To assess the performance of clinical risk factors, uterine artery Doppler and angiogenic markers to predict preterm pre‐eclampsia in nulliparous women.

MMP-2 Levels are Elevated in the Plasma of Women Who Subsequently Develop Preeclampsia

Objective. To determine levels of matrix metalloproteinase (MMP)-2 and MMP-9, and the tissue inhibitors of metalloproteinases (TIMP)-1 and TIMP-2 in the plasma of women destined to develop preeclampsia prior to the onset of clinical disease. Study Design. Plasma samples were taken from women whose pregnancies were subsequently complicated by preeclampsia and from normal pregnant women at 22 and 26 weeks and at delivery or diagnosis. Following equal protein loading, MMP-2 and 9 and TIMP–1 and 2 were quantified using zymography and Western blot analysis, respectively. Results. Plasma MMP-2 levels were significantly elevated at 22 weeks (p = 0.02) and at diagnosis (p = 0.003) in the preeclampsia group, but there was no difference at 26 weeks. TIMP-1 levels were significantly reduced in the preeclampsia group at 26 weeks (p = 0.0002), but TIMP-2 levels were not quantifiable. Conclusion. At all three gestational time points an imbalance in the MMP-2:TIMP-1 ratio was found in patients who subsequently developed preeclampsia. We speculate that increased net MMP-2 activity may contribute to the endothelial dysfunction that is central to the pathophysiology of preeclampsia.

In Preeclampsia, the Circulating Factors Capable of Altering In Vitro Endothelial Function Precede Clinical Disease

The pathophysiology of preeclampsia involves the release of a circulating factor(s) from a hypoperfused placenta that activates the maternal endothelium. This study investigated the effect on in vitro endothelial function of plasma taken from women in whom preeclampsia subsequently developed. Women at increased risk for an adverse pregnancy outcome were identified using Doppler waveform analysis. Plasma samples (22 and 26 weeks) were incubated with myometrial vessels taken from women with uncomplicated pregnancies. Wire myography was used to study the effect of plasma on the endothelium-dependent vessel behavior. Incubation of vessels from normal pregnant women with plasma from women in whom preeclampsia subsequently developed (n=19) significantly reduced endothelium-dependent relaxation, compared with vessels incubated with plasma from normal pregnant women (n=48). This effect was demonstrable for plasma taken at 22 weeks (residual constriction 47.1±6.6% versus 32.0±4.4%, P=0.004 at 1-hour incubation; and 59.1±8.4% versus 42.3±5.9%, P=0.001 at 18-hour incubation) and 26 weeks (59.2±5.2% versus 29.1±5.6%, P<0.001 at 1 hour; and 63.3±7.6% versus 31.9 +/-7.2%, P<0.0001 at 18 hours). Endothelial-dependent relaxation was unaltered after incubation with plasma taken from women in whom normotensive intrauterine growth restriction subsequently developed (n=19). This study supports the hypothesis that plasma, from women in whom preeclampsia develops, collected weeks before diagnosis is capable of altering endothelial function.

Hypertensive diseases and eclampsia

Worldwide, pre-eclampsia and eclampsia contribute to the death of a pregnant woman every 3 min. In the UK in recent decades, hypertensive disorders of pregnancy have remained one of the leading causes of both maternal and perinatal morbidity and mortality. The management of pregnancies complicated by hypertension has not significantly altered for many years, possibly as a result of little progress being made in our understanding of the condition. New insights, however, have recently been gained into the pathophysiology of pre-eclampsia. These have yet to be translated into new interventions or to make any impact on clinical management of these pregnancies. This review will therefore focus on recent advances relating to research into the aetiology and pathogenesis of pre-eclampsia, but will conclude with a brief update on current therapeutic strategies.

Integrated proteomics pipeline yields novel biomarkers for predicting preeclampsia

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.

Regulation of Endothelial-Dependent Relaxation in Human Systemic Arteries by SKCa and IKCa Channels:

Blockade of small-conductance Ca 2 + -activated K + channels (SK Ca ) and intermediate conductance Ca 2 + -activated K + channels (IK Ca ) can cause inhibition of endothelium-dependent hyperpolarizing factor (EDHF) in many vascular beds from animals, but there is a relative paucity of data in human vessels. Systemic arteries, isolated from women with healthy pregnancies, relax to the endothelial-dependent agonist bradykinin via a nonprostacyclin and non–nitric oxide pathway attributable to EDHF. Therefore, in this study, the authors investigated the effect of pharmacological blockade of SK Ca and IK Ca on EDHF-mediated relaxation of human omental and myometrial arteries preconstricted with either arginine vasopressin or U46619. Human arteries were isolated from omental and myometrial biopsies taken from healthy women undergoing planned cesarean section at term. Endothelial function was assessed using wire myography. In all vessels examined, nonspecific blockade of IK Ca with charybdotoxin attenuated EDHF-attributed relaxation. However, when Tram 34 was used to block IK Ca , the attenuation of relaxation was evident only with U46619 preconstriction. In arteries from both vascular beds, and with either preconstrictor, a combination of either apamin and charybdotoxin or apamin plus Tram 34 almost ablated EDHF-attributable relaxation. These data support the notion that in human systemic arteries, activation of, primarily, SK Ca and IK Ca K + channel subtypes underlies EDHF-mediated relaxation. These results have important implications for future studies ascertaining the molecular mechanisms of hypertensive disorders (eg, preeclampsia, in which EDHF is thought to be aberrant).

A Label-free Selected Reaction Monitoring Workflow Identifies a Subset of Pregnancy Specific Glycoproteins as Potential Predictive Markers of Early-onset Pre-eclampsia

Pre-eclampsia (PE) is a serious complication of pregnancy with potentially life threatening consequences for both mother and baby. Presently there is no test with the required performance to predict which healthy first-time mothers will go on to develop PE. The high specificity, sensitivity, and multiplexed nature of selected reaction monitoring holds great potential as a tool for the verification and validation of putative candidate biomarkersfor disease states. Realization of this potential involves establishing a high throughput, cost effective, reproducible sample preparation workflow. We have developed a semi-automated HPLC-based sample preparation workflow before a label-free selected reaction monitoring approach. This workflow has been applied to the search for novel predictive biomarkers for PE. To discover novel candidate biomarkers for PE, we used isobaric tagging to identify several potential biomarker proteins in plasma obtained at 15 weeks gestation from nulliparous women who later developed PE compared with pregnant women who remained healthy. Such a study generates a number of “candidate” biomarkers that require further testing in larger patient cohorts. As proof-of-principle, two of these proteins were taken forward for verification in a 100 women (58 PE, 42 controls) using label-free SRM. We obtained reproducible protein quantitation across the 100 samples and demonstrated significant changes in protein levels, even with as little as 20% change in protein concentration. The SRM data correlated with a commercial ELISA, suggesting that this is a robust workflow suitable for rapid, affordable, label-free verification of which candidate biomarkers should be taken forward for thorough investigation. A subset of pregnancy-specific glycoproteins (PSGs) had value as novel predictive markers for PE.