Prediction of preeclampsia with angiogenic biomarkers. Results from the prospective Odense Child Cohort

High-Sensitivity Cardiac Troponin I Enhances Preeclampsia Prediction Beyond Maternal Factors and the sFlt-1/PlGF Ratio

BACKGROUND

Preeclampsia shares numerous risk factors with cardiovascular diseases. Here, we aimed to assess the potential utility of high-sensitivity cardiac troponin I (hs-cTnI) values during pregnancy in predicting preeclampsia occurrence.

METHODS

This study measured hs-cTnI levels in 3721 blood samples of 2245 pregnant women from 4 international, prospective cohorts. Three analytical approaches were used: (1) a cross-sectional analysis of all women using a single blood sample, (2) a longitudinal analysis of hs-cTnI trajectories in women with multiple samples, and (3) analyses of prediction models incorporating hs-cTnI, maternal factors, and the sFlt-1 (soluble fms-like tyrosine kinase 1)/PlGF (placental growth factor) ratio.

RESULTS

Women with hs-cTnI levels in the upper quarter had higher odds ratios for preeclampsia occurrence compared with women with levels in the lower quarter. Associations were driven by preterm preeclampsia (odds ratio, 5.78 [95% CI, 2.73-12.26]) and remained significant when using hs-cTnI as a continuous variable adjusted for confounders. Between-trimester hs-cTnI trajectories were independent of subsequent preeclampsia occurrence. A prediction model incorporating a practical hs-cTnI level of detection cutoff (≥1.9 pg/mL) alongside maternal factors provided comparable performance with the sFlt-1/PlGF ratio. A comprehensive model including sFlt-1/PlGF, maternal factors, and hs-cTnI provided added value (cross-validated area under the receiver operator characteristic, 0.78 [95% CI, 0.73-0.82]) above the sFlt-1/PlGF ratio alone (cross-validated area under the receiver operator characteristic, 0.70 [95% CI, 0.65-0.76]; P=0.027). As assessed by likelihood ratio tests, the addition of hs-cTnI to each prediction model significantly improved the respective prediction model not incorporating hs-cTnI, particularly for preterm preeclampsia. Net reclassification improvement analyses indicated that incorporating hs-cTnI improved risk prediction predominantly by correctly reclassifying women with subsequent preeclampsia occurrence.

CONCLUSIONS

These exploratory findings uncover a potential role for hs-cTnI as a complementary biomarker in the prediction of preeclampsia. After validation in prospective studies, hs-cTnI, alongside maternal factors, may either be considered as a substitute for angiogenic biomarkers in health care systems where they are sparce or unavailable, or as an enhancement to established prediction models using angiogenic markers.

Accuracy of placental growth factor alone or in combination with soluble fms-like tyrosine kinase-1 or maternal factors in detecting preeclampsia in asymptomatic women in the second and third trimesters: a systematic review and meta-analysis

OBJECTIVE

This study aimed to: (1) identify all relevant studies reporting on the diagnostic accuracy of maternal circulating placental growth factor) alone or as a ratio with soluble fms-like tyrosine kinase-1), and of placental growth factor-based models (placental growth factor combined with maternal factors±other biomarkers) in the second or third trimester to predict subsequent development of preeclampsia in asymptomatic women; (2) estimate a hierarchical summary receiver-operating characteristic curve for studies reporting on the same test but different thresholds, gestational ages, and populations; and (3) select the best method to screen for preeclampsia in asymptomatic women during the second and third trimester of pregnancy by comparing the diagnostic accuracy of each method.

DATA SOURCES

A systematic search was performed through MEDLINE, Embase, CENTRAL, ClinicalTrials.gov, and the World Health Organization International Clinical Trials Registry Platform databases from January 1, 1985 to April 15, 2021.

STUDY ELIGIBILITY CRITERIA

Studies including asymptomatic singleton pregnant women at >18 weeks' gestation with risk of developing preeclampsia were evaluated. We included only cohort or cross-sectional test accuracy studies reporting on preeclampsia outcome, allowing tabulation of 2×2 tables, with follow-up available for >85%, and evaluating performance of placental growth factor alone, soluble fms-like tyrosine kinase-1- placental growth factor ratio, or placental growth factor-based models. The study protocol was registered on the International Prospective Register Of Systematic Reviews (CRD 42020162460).

METHODS

Because of considerable intra- and interstudy heterogeneity, we computed the hierarchical summary receiver-operating characteristic plots and derived diagnostic odds ratios, β, θi, and Λ for each method to compare performances. The quality of the included studies was evaluated by the QUADAS-2 tool.

RESULTS

The search identified 2028 citations, from which we selected 474 studies for detailed assessment of the full texts. Finally, 100 published studies met the eligibility criteria for qualitative and 32 for quantitative syntheses. Twenty-three studies reported on performance of placental growth factor testing for the prediction of preeclampsia in the second trimester, including 16 (with 27 entries) that reported on placental growth factor test alone, 9 (with 19 entries) that reported on the soluble fms-like tyrosine kinase-1-placental growth factor ratio, and 6 (16 entries) that reported on placental growth factor-based models. Fourteen studies reported on performance of placental growth factor testing for the prediction of preeclampsia in the third trimester, including 10 (with 18 entries) that reported on placental growth factor test alone, 8 (with 12 entries) that reported on soluble fms-like tyrosine kinase-1-placental growth factor ratio, and 7 (with 12 entries) that reported on placental growth factor-based models. For the second trimester, Placental growth factor-based models achieved the highest diagnostic odds ratio for the prediction of early preeclampsia in the total population compared with placental growth factor alone and soluble fms-like tyrosine kinase-1-placental growth factor ratio (placental growth factor-based models, 63.20; 95% confidence interval, 37.62-106.16 vs soluble fms-like tyrosine kinase-1-placental growth factor ratio, 6.96; 95% confidence interval, 1.76-27.61 vs placental growth factor alone, 5.62; 95% confidence interval, 3.04-10.38); placental growth factor-based models had higher diagnostic odds ratio than placental growth factor alone for the identification of any-onset preeclampsia in the unselected population (28.45; 95% confidence interval, 13.52-59.85 vs 7.09; 95% confidence interval, 3.74-13.41). For the third trimester, Placental growth factor-based models achieved prediction for any-onset preeclampsia that was significantly better than that of placental growth factor alone but similar to that of soluble fms-like tyrosine kinase-1-placental growth factor ratio (placental growth factor-based models, 27.12; 95% confidence interval, 21.67-33.94 vs placental growth factor alone, 10.31; 95% confidence interval, 7.41-14.35 vs soluble fms-like tyrosine kinase-1-placental growth factor ratio, 14.94; 95% confidence interval, 9.42-23.70).

CONCLUSION

Placental growth factor with maternal factors ± other biomarkers determined in the second trimester achieved the best predictive performance for early preeclampsia in the total population. However, in the third trimester, placental growth factor-based models had predictive performance for any-onset preeclampsia that was better than that of placental growth factor alone but similar to that of soluble fms-like tyrosine kinase-1-placental growth factor ratio. Through this meta-analysis, we have identified a large number of very heterogeneous studies. Therefore, there is an urgent need to develop standardized research using the same models that combine serum placental growth factor with maternal factors ± other biomarkers to accurately predict preeclampsia. Identification of patients at risk might be beneficial for intensive monitoring and timing delivery.

Combination of Maternal Serum ESM-1 and PLGF with Uterine Artery Doppler PI for Predicting Preeclampsia

OBJECTIVE

This study aimed to determine whether the combination of pregnancy-associated endothelial cell-specific molecule 1 (ESM-1), the placental growth factor (PLGF) in the first- and second-trimester maternal serum, and the uterine artery Doppler pulsatility index (PI) in the second trimester can predict preeclampsia (PE).

METHODS

The serum levels of ESM-1 and PLGF in 33 severe preeclampsia (SPE) patients, 18 mild preeclampsia patients (MPE), and 60 age-matched normal controls (CON) were measured. The Doppler ultrasonography was performed, and the artery pulsatility index (PI) was calculated for the same subjects.

RESULTS

The 2nd PLGF level was significantly lower and the 2nd PI was higher than those in the MPE group. Combining the 2nd PLGF with the 2nd PI yielded an AUC of 0.819 (83.33% sensitivity and 70.00% specificity). In the SPE group, the 1st ESM-1 level and the 2nd PLGF level were significantly lower, and the 2nd ESM-1 level and the 2nd PI were significantly higher in the SPE group. The combination of the 1st ESM-1, the 2nd PLGF, and the 2nd PI yielded an AUC of 0.912 (72.73% sensitivity and 95.00% specificity).

CONCLUSIONS

The 1st ESM-1 and the 2nd PLGF levels and the 2nd PI were associated with PE. The combination of serum biomarkers and the PI improved the screening efficiency of the PE prediction, especially for SPE.

The prognostic utility of soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PIGF) biomarkers for predicting preeclampsia: a secondary analysis of data from the INSPIRE trial

Objective

To compare the prognostic performance of biomarkers soluble fms-like tyrosine kinase-1 (sFlt-1), Placental Growth Factor (PIGF), and sFlt-1/PIGF ratio as continuous values or as a binary cut-off of 38 for predicting preeclampsia (PE) within 7 days.

Design

Secondary analysis of a randomised clinical trial.

Setting

Oxford University Hospitals, Oxford, United Kingdom (UK).

Population

Pregnant women between 24⁺⁰ to 37⁺⁰ weeks of gestation with a clinical suspicion of preeclampsia.

Main outcome

Onset of preeclampsia within 7 days of the initial biomarker test.

Methods

Logistic regression model for onset of preeclampsia using: (i) sFlt-1 (ii) PIGF, (iii) sFlt-1/PIGF ratio (continuous), and (iv) sFlt-1/PIGF ratio as a cut-off above or below 38.

Results

Of the total 370 women, 42 (11.3%) developed PE within 7 days of screening. Models with sFlt-1 and sFlt-1/PIGF ratio (continuous) had greater overall performance than models with PIGF or with sFlt-1/PIGF ratio as a cut-off at 38 (R²: sFlt-1 = 55%, PIGF = 38%, sFlt-1/PIGF ratio = 57%, sFlt-1/PIGF ratio as cut-off at 38 model = 46%). The discrimination performance was the highest in sFlt-1 and sFlt-1/PIGF ratio (continuous) (c-statistic, sFlt-1 = 0.94, sFlt-1/PIGF ratio (continuous) = 0.94) models compared to PIGF or sFlt-1/PIGF cut-off models (c-statistic, PIGF = 0.87, sFlt-1/PIGF cut-off = 0.89).

Conclusion

Models using continuous values of sFlt-1 only or sFlt-1/PIGF ratio had better predictive performance compared to a PIGF only or the model with sFlt-1/PIGF ratio as a cut-off at 38. Further studies based on a larger sample size are warranted to substantiate this finding.

External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis

OBJECTIVE

Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance.

METHODS

MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit.

RESULTS

Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes.

CONCLUSIONS

The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: an individual participant data meta-analysis

BACKGROUND

Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management.

OBJECTIVES

To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers.

DESIGN

This was an individual participant data meta-analysis of cohort studies.

SETTING

Source data from secondary and tertiary care.

PREDICTORS

We identified predictors from systematic reviews, and prioritised for importance in an international survey.

PRIMARY OUTCOMES

Early-onset (delivery at < 34 weeks' gestation), late-onset (delivery at ≥ 34 weeks' gestation) and any-onset pre-eclampsia.

ANALYSIS

We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration. We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of ≥ 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I ² and τ². A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals.

RESULTS

The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C-statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-eclampsia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-eclampsia.

LIMITATIONS

Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the individual participant data.

CONCLUSION

For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings.

FUTURE WORK

Recalibration of model parameters within populations may improve calibration performance. Additional strong predictors need to be identified to improve model performance and consistency. Validation, including examination of calibration heterogeneity, is required for the models we could not validate.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42015029349.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 72. See the NIHR Journals Library website for further project information.

Women's attitudes, beliefs and values about tests, and management for hypertensive disorders of pregnancy

BACKGROUND

Advances in research suggest the possibility of improving routine clinical care for preeclampsia using screening (predictive) and diagnostic tests. The views of women should be incorporated into the way in which such tests are used. Therefore, we explored the views of women with experience of preeclampsia and other hypertensive disorders in pregnancy (HDPs) about predictive and diagnostic tests, treatment risks, and expectant management.

METHOD

Eight hundred and seven women with experience of preeclampsia or other HDPs completed an online questionnaire. These women were participants in the Preeclampsia Registry (USA). The questionnaire contained 22 items to elicit women's views about predictive tests (n = 8); diagnostic tests (n = 5); treatment risks (n = 7), and expectant management (n = 2). An optional text box allowed participants to add qualitative open-ended comments. Levels of agreement with the statements were reported descriptively for the sample as a whole, and a preliminary investigation of the role of lived experience in shaping women's views was conducted by comparing subgroups within the sample based on time of HDP delivery (preterm/term). The qualitative data provided in the optional text box was analysed using inductive thematic analysis to examine participants' responses.

RESULTS

Women generally favored predictive and diagnostic testing, although not because they would opt for termination of pregnancy. Participants generally disagreed that taking daily low-dose aspirin (LDA) would make them nervous, with disagreement significantly higher in the preterm delivery subgroup. A high proportion of participants, especially in the preterm delivery subgroup, would take LDA throughout pregnancy. The majority of participants would be more worried about the possibility of preeclampsia than about the risks of treatments to their health (60%), and that proportion was significantly higher in the preterm delivery subgroup. There were no differences between subgroups in the views expressed about expectant management, although opinion was divided in both groups. Overall, most participants opted to put the baby's interests first.

CONCLUSION

Women with experience of hypertensive disorders were enthusiastic about improved predictive and diagnostic tests. However, varied views about treatment options and expectant management suggest the need for a shared decision-making tool to enable healthcare professionals to support pregnant women's decision-making to maximize the utility of these tests and interventions.

Routinely collected antenatal data for longitudinal prediction of preeclampsia in nulliparous women: a population-based study

The objective was to evaluate the sequentially updated predictive capacity for preeclampsia during pregnancy, using multivariable longitudinal models including data from antenatal care. This population-based cohort study in the Stockholm-Gotland Counties, Sweden, included 58,899 pregnancies of nulliparous women 2008-2013. Prospectively collected data from each antenatal care visit was used, including maternal characteristics, reproductive and medical history, and repeated measurements of blood pressure, weight, symphysis-fundal height, proteinuria, hemoglobin and blood glucose levels. We used a shared-effects joint longitudinal model including all available information up until a given gestational length (week 24, 28, 32, 34 and 36), to update preeclampsia prediction sequentially. Outcome measures were prediction of preeclampsia, preeclampsia with delivery < 37, and preeclampsia with delivery ≥ 37 weeks' gestation. The area under the curve (AUC) increased with gestational length. AUC for preeclampsia with delivery < 37 weeks' gestation was 0.73 (95% CI 0.68-0.79) at week 24, and increased to 0.87 (95% CI 0.84-0.90) in week 34. For preeclampsia with delivery ≥ 37 weeks' gestation, the AUC in week 24 was 0.65 (95% CI 0.63-0.68), but increased to 0.79 (95% CI 0.78-0.80) in week 36. The addition of routinely collected clinical measurements throughout pregnancy improve preeclampsia prediction and may be useful to individualize antenatal care.

Placenta morphology and biomarkers in pregnancies with congenital heart disease - A systematic review

Impaired placentation is an important contributing factor to intra-uterine growth restriction and pre-eclampsia in fetuses with congenital heart defects (CHD). These pregnancy complications occur more frequently in pregnancies with fetal CHD. One of the most important factors influencing the life of children with CHD is neurodevelopmental delay, which seems to start already in utero. Delayed neurodevelopment in utero may be correlated or even (partly) explained by impaired placentation in CHD cases. This systematic review provides an overview of published literature on placental development in pregnancies with fetal CHD. A systematic search was performed and the Newcastle-Ottawa scale was used to access data quality. Primary outcomes were placenta size and weight, vascular and villous architecture, immunohistochemistry, angiogenic biomarkers and/or placental gene expression. A total of 1161 articles were reviewed and 21 studies were included. Studies including CHD with a genetic disorder or syndrome and/or multiple pregnancies were excluded. Lower placental weight and elevated rates of abnormal umbilical cord insertions were found in CHD. Cases with CHD more frequently showed microscopic placental abnormalities (i.e. abnormal villous maturation and increased maternal vascular malperfusion lesions), reduced levels of angiogenic biomarkers and increased levels of anti-angiogenic biomarkers in maternal serum and umbilical cord blood. Altered gene expression involved in placental development and fetal growth were found in maternal serum and CHD placentas. In conclusion, abnormal placentation is found in CHD. More extensive studies are needed to elucidate the contribution of impaired placentation to delayed neurodevelopment in CHD cases.

The ROBINS-I and the NOS had similar reliability but differed in applicability: A random sampling observational studies of systematic reviews/meta-analysis

OBJECTIVE

There is a lack of evidence on the usage of the quality assessment tool-the Risk Of Bias In Nonrandomized Studies-of Interventions (ROBINS-I). This article aimed to measure the reliability, criterion validity, and feasibility of the ROBINS-I and the Newcastle-Ottawa Scale (NOS).

METHODS

A sample of systematic reviews or meta-analyses of observational studies were selected from Medline (2013-2017) and assessed by two reviewers using ROBINS-I and the NOS. We reported on reliability in terms of the first-order agreement coefficient (AC1) statistic. Correlation coefficient statistic was used to explore the criterion validity of the ROBINS-I. We compared the feasibility of the ROBINS-I and NOS by recording the time to complete an assessment and the instances where assessing was difficult.

RESULTS

Five systematic reviews containing 41 cohort studies were finally included. Interobserver agreement on the individual domain of the ROBINS-I as well as the NOS was substantial with a mean AC1 statistic of 0.67 (95% CI: 0.50-0.83) and 0.73 (95% CI: 0.65-0.81), respectively. The criterion validity of the ROBNS-I was moderate (K = 0.52) against NOS. The time in assessing a single study by ROBINS-I varied from 7 hours initially to 3 hours compared with 30 minutes for the NOS. Both reviewers rated "bias due to departure from the intended interventions" the most time-consuming domain in the ROBINS-I, items in the NOS were equal.

CONCLUSIONS

The ROBINS-I and the NOS seem to provide the same reliability but vary in applicability. The over-complicated feature of ROBINS-I may limit its usage and a simplified version is needed.

Proteomic signatures predict preeclampsia in individual cohorts but not across cohorts - implications for clinical biomarker studies

Background:

Early identification of pregnant women at risk for preeclampsia (PE) is important, as it will enable targeted interventions ahead of clinical manifestations. The quantitative analyses of plasma proteins feature prominently among molecular approaches used for risk prediction. However, derivation of protein signatures of sufficient predictive power has been challenging. The recent availability of platforms simultaneously assessing over 1000 plasma proteins offers broad examinations of the plasma proteome, which may enable the extraction of proteomic signatures with improved prognostic performance in prenatal care.

Objective:

The primary aim of this study was to examine the generalizability of proteomic signatures predictive of PE in two cohorts of pregnant women whose plasma proteome was interrogated with the same highly multiplexed platform. Establishing generalizability, or lack thereof, is critical to devise strategies facilitating the development of clinically useful predictive tests. A second aim was to examine the generalizability of protein signatures predictive of gestational age (GA) in uncomplicated pregnancies in the same cohorts to contrast physiological and pathological pregnancy outcomes.

Study design:

Serial blood samples were collected during the first, second, and third trimesters in 18 women who developed PE and 18 women with uncomplicated pregnancies (Stanford cohort). The second cohort (Detroit), used for comparative analysis, consisted of 76 women with PE and 90 women with uncomplicated pregnancies. Multivariate analyses were applied to infer predictive and cohort-specific proteomic models, which were then tested in the alternate cohort. Gene ontology (GO) analysis was performed to identify biological processes that were over-represented among top-ranked proteins associated with PE.

Results:

The model derived in the Stanford cohort was highly significant (p = 3.9E–15) and predictive (AUC = 0.96), but failed validation in the Detroit cohort (p = 9.7E–01, AUC = 0.50). Similarly, the model derived in the Detroit cohort was highly significant (p = 1.0E–21, AUC = 0.73), but failed validation in the Stanford cohort (p = 7.3E–02, AUC = 0.60). By contrast, proteomic models predicting GA were readily validated across the Stanford (p = 1.1E–454, R = 0.92) and Detroit cohorts (p = 1.1.E–92, R = 0.92) indicating that the proteomic assay performed well enough to infer a generalizable model across studied cohorts, which makes it less likely that technical aspects of the assay, including batch effects, accounted for observed differences.

Conclusions:

Results point to a broader issue relevant for proteomic and other omic discovery studies in patient cohorts suffering from a clinical syndrome, such as PE, driven by heterogeneous pathophysiologies. While novel technologies including highly multiplex proteomic arrays and adapted computational algorithms allow for novel discoveries for a particular study cohort, they may not readily generalize across cohorts. A likely reason is that the prevalence of pathophysiologic processes leading up to the “same” clinical syndrome can be distributed differently in different and smaller-sized cohorts. Signatures derived in individual cohorts may simply capture different facets of the spectrum of pathophysiologic processes driving a syndrome. Our findings have important implications for the design of omic studies of a syndrome like PE. They highlight the need for performing such studies in diverse and well-phenotyped patient populations that are large enough to characterize subsets of patients with shared pathophysiologies to then derive subset-specific signatures of sufficient predictive power.

Predictive Performance of PlGF (Placental Growth Factor) for Screening Preeclampsia in Asymptomatic Women: A Systematic Review and Meta-Analysis

Preeclampsia is a systemic syndrome that seems to originate from the placenta and is associated with an imbalance between angiogenic factors in the maternal circulation. One of the well-studied and widely used factors is PlGF (placental growth factor), the levels of which drop in women destined to develop preeclampsia. This drop is known to precede the development of actual signs and symptoms of preeclampsia, thus proving to be a useful screening tool in predicting the disease. The literature varies widely in terms of the clinical usefulness of the test. We conducted a meta-analysis to study the predictive accuracy of PlGF in asymptomatic women. Our analysis included 40 studies with 3189 cases of preeclampsia and 89 498 controls. The overall predictive odds ratio of the test was 9 (6-13). Subgroup analysis evaluating various PlGF thresholds demonstrated that the predictive values were highest for PlGF levels between 80 and 120 pg/mL with a high predictive odds ratio of 25 (7-88), a sensitivity of 0.78 (95% CI, 0.67-0.86), a specificity of 0.88 (95% CI, 0.75-0.95), a positive likelihood ratio of 6.3 (95% CI, 2.7-14.7), and a negative likelihood ratio of 0.26 (95% CI, 0.16-0.42). Additionally, the accuracy was higher when the test was performed after 14 weeks of gestation (OR, 10 [7-15]) and for prediction of early onset preeclampsia (OR, 18 [9-37]). We conclude that PlGF is a useful screening tool to predict preeclampsia. Nonetheless, its utility should be judged with caution and randomized controlled trials are warranted to explore if its implementation improves perinatal outcomes in asymptomatic women.

Aldosterone, Salt, and Potassium Intakes as Predictors of Pregnancy Outcome, Including Preeclampsia

The mineralocorticoid aldosterone increases in plasma in healthy pregnancy along with renin and angiotensin II and plays a key role in the physiological plasma volume expansion. In mice, aldosterone contributes to an optimal fetal development by enhancing PlGF (placental growth factor) expression and trophoblast cell proliferation. In preeclampsia, there is coincident suppression of aldosterone and impaired placental development. We hypothesized that aldosterone independently contributes to placental and birth weight in humans, and high dietary sodium and low potassium intakes affect this relationship adversely. We analyzed 24-hour urine collections and plasma samples from gestational week 29 in a subsample of 569 pregnant women from the Odense Child Cohort-a Danish population-based longitudinal cohort study. Plasma and urinary aldosterone were measured by ELISA, sodium and potassium excretions by flame photometer. Predictive values of aldosterone levels and sodium and potassium intakes were assessed by multiple and Cox regression analyses. Primary outcomes were placental weight and birth weight. Secondary outcome was preeclampsia. Urinary aldosterone excretion at gestational week 29 independently contributed to placental and birth weights (adjusted β-coefficients [95% CI], 24.50 [9.66-39.35] and 9.59 [4.57-14.61], respectively). Aldosterone levels were not associated to preeclampsia incidence. Salt intake >6 g/d was associated with development of preeclampsia (hazard ratio [95% CI], 5.68 [1.51-21.36]). At gestational week 29, urinary aldosterone excretion is an independent predictor of placental and birth weights. High salt intake is a risk factor for preeclampsia. In perspective, suppression of aldosterone in pregnancy has adverse trophic effects.

Prediction models for preeclampsia: A systematic review

BACKGROUND

Preeclampsia is a disease specific to pregnancy that can cause severe maternal and foetal morbidity and mortality. Early identification of women at higher risk for preeclampsia could potentially aid early prevention and treatment. Although a plethora of preeclampsia prediction models have been developed in recent years, individualised prediction of preeclampsia is rarely used in clinical practice.

OBJECTIVES

The objective of this systematic review was to provide an overview of studies on preeclampsia prediction.

STUDY DESIGN

Relevant research papers were identified through a MEDLINE search up to 1 January 2017. Prognostic studies on the prediction of preeclampsia or preeclampsia-related disorders were included. Quality screening was performed with the Quality in Prognostic Studies (QUIPS) tool.

RESULTS

Sixty-eight prediction models from 70 studies with 425,125 participants were selected for further review. The number of participants varied and the gestational age at prediction varied widely across studies. The most frequently used predictors were medical history, body mass index, blood pressure, parity, uterine artery pulsatility index, and maternal age. The type of predictor (maternal characteristics, ultrasound markers and/or biomarkers) was not clearly associated with model discrimination. Few prediction studies were internally (4%) or externally (6%) validated.

CONCLUSIONS

To date, multiple and widely varying models for preeclampsia prediction have been developed, some yielding promising results. The high degree of between-study heterogeneity impedes selection of the best model, or an aggregated analysis of prognostic models. Before multivariable preeclampsia prediction can be clinically implemented universally, further validation and calibration of well-performing prediction models is needed.

Prediction of birth weight small for gestational age with and without preeclampsia by angiogenic markers: an Odense Child Cohort study

Purpose: To investigate the predictive performance of placental growth factor (PlGF) and soluble FMS-like kinase 1 (sFlt-1) on birth weight and small for gestational age (SGA), in a large, population-based cohort.Methods: Women enrolled in the population-based, prospective Odense Child Cohort Study with early (GA < 20 weeks) and/or late (≥20 weeks) pregnancy blood samples (n = 1937) were included. The association between log-transformed values of the biomarkers and birth weight Z-score was studied using multivariate regression models. The prediction of SGA overall, and in women developing preeclampsia, by biomarkers was evaluated using receiver operating characteristic analyses.Results: No substantial associations between early pregnancy biomarkers and SGA were seen. PlGF measured in late pregnancy demonstrated the strongest association with birth weight Z-score (adjusted β-coefficient = 0.43 [95%CI = 0.35; 0.50]). The area under curve (AUC) for predicting SGA was higher for sFlt-1/PlGF compared to sFlt-1 (0.74 versus 0.63, p = .006) and reached excellent prediction for SGA after preeclampsia (AUC 0.94). Optimal sFlt-1/PlGF ratio cut-offs had higher negative predictive value (NPV) and positive predictive value (PPV) for SGA (cut-off > 5.0; NPV = 99.1%, PPV = 5.4%) compared to each marker individually.Conclusion: The sFlt-1/PlGF ratio is a potential predictor of SGA in population-based screening, particularly when preeclampsia is also present.

Angiogenic and Antiangiogenic Markers for Prediction and Risk Classification of Preeclampsia

Preeclampsia is a pregnancy-specific hypertensive disorder with multisystem involvement and is a significant cause of obstetric morbidity and mortality worldwide. A major issue in the treatment of preeclampsia stems from its still significant rates of misclassification and misdiagnosis. Angiogenic factors have been speculated as a possible diagnostic modality due to a perceived imbalance in angiogenesis in preeclampsia. Factors currently studied include soluble fms-like protein kinase 1 and placental growth factor. Because of significant mortality associated with preeclampsia it is felt that both early and accurate diagnosis of preeclampsia is imperative if this disease process is to be treated.

Placental-specific sFLT-1: role in pre-eclamptic pathophysiology and its translational possibilities for clinical prediction and diagnosis

Pre-eclampsia is a common obstetric complication globally responsible for a significant burden of maternal and perinatal morbidity and mortality. Central to its pathophysiology is the anti-angiogenic protein, soluble fms-like tyrosine kinase-1 (sFLT-1). sFLT-1 is released from a range of tissues into the circulation, where it antagonizes the activity of vascular endothelial growth factor and placental growth factor leading to endothelial dysfunction. It is this widespread endothelial dysfunction that produces the clinical features of pre-eclampsia including hypertension and proteinuria. There are multiple splice variants of sFLT-1. One, known as sFLT-1 e15a, evolved quite recently and is only present in humans and higher order primates. This sFLT-1 variant is also the main sFLT-1 secreted from the placenta. Recent work has shown that sFLT-1 e15a is significantly elevated in the placenta and circulation of women with pre-eclampsia. It is also biologically active, capable of causing endothelial dysfunction and the end-organ dysfunction seen in pre-eclampsia. Indeed, the over-expression of sFLT-1 e15a in mice recapitulates the pre-eclamptic phenotype in pregnancy. Therefore, here we propose that sFLT-1 e15a may be the sFLT-1 variant primarily responsible for pre-eclampsia, a uniquely human disease. Furthermore, this placental-specific sFLT-1 variant provides promise for use as an accurate biomarker in the prediction or diagnosis of pre-eclampsia.

Podocyturia as an early diagnostic marker of preeclampsia: a literature review

CONTEXT

Preeclampsia (PE) is a pregnancy-related disease, and it is a leading cause of maternal and neonatal morbidity and mortality. It is characterized by the new onset of hypertension after 20 weeks of gestation together with signs of organ damage, most commonly the kidneys. The treatment of PE is symptomatic and final intervention requires delivery, regardless of the gestational age of the foetus. Furthermore, PE is a risk factor for developing cardiovascular disease and chronic kidney disease - even many years after the delivery.

OBJECTIVE

Current research of PE has revealed that detection of podocytes in urine (podocyturia) could be a useful method for both confirmation of PE diagnosis and for the prediction of the severity of the disease.

CONCLUSION

The main aim of this review is to summarize the current state of available methods for podocyte detection and to discuss their relevance in clinical practice.

Blood laboratory testing for early prediction of preeclampsia: chasing the finish line or at the starting blocks?

Preeclampsia (PE) affects 2-8% of pregnancies worldwide, thus representing an important cause of maternal and neonatal morbidity, up to death. Many studies have been designed to identify putative biomarkers for accurate and timely diagnosing PE, but only some of them were focused on specific and sensitive biomarkers for early prediction of this life-threatening condition. In particular, some prospective studies aimed to investigate the predictive role of circulating biomarkers before 20 weeks of gestation in the general pregnant population yielded conflicting results. This article is hence centered on results obtained in studies investigating the predictive performances of angiogenic, anti-angiogenic, inflammatory, endocrine, and epigenetic biomarkers. The available evidence suggests that angiogenic and anti-angiogenic molecules, in particular the sFlt1:PlGF ratio, may be considered the biomarkers with the best diagnostic performance in the second trimester. However, doubts remain about their use in clinical settings before the 20th gestational week. Even lower evidence is available for other biomarkers, due to the fact that some positive results have not been confirmed in ensuing investigations, whereas unresolved analytical issues still contribute to make their clinical reliability rather questionable. Differential expression of microRNAs seems also a promising evidence for early prediction of PE, but additional research and well-designed prospective studies are needed to identify and validate routine predictive tests. KEY MESSAGES Preeclampsia affects 2-8% of pregnant women worldwide, thus remaining one of the leading causes of maternal and neonatal morbidity and mortality. Several studies have investigated the predictive role of circulating biomarkers before 20th week of gestation with conflicting results. Additional research and well-designed prospective studies are needed to identify and validate predictive tests in clinical practice.

Vascular adaptation in pregnancy and endothelial dysfunction in preeclampsia

Maternal vascular adaptation to pregnancy is critically important to expand the capacity for blood flow through the uteroplacental unit to meet the needs of the developing fetus. Failure of the maternal vasculature to properly adapt can result in hypertensive disorders of pregnancy such as preeclampsia (PE). Herein, we review the endocrinology of maternal adaptation to pregnancy and contrast this with that of PE. Our focus is specifically on those hormones that directly influence endothelial cell function and dysfunction, as endothelial cell dysfunction is a hallmark of PE. A variety of growth factors and cytokines are present in normal vascular adaptation to pregnancy. However, they have also been shown to be circulating at abnormal levels in PE pregnancies. Many of these factors promote endothelial dysfunction when present at abnormal levels by acutely inhibiting key Ca²⁺ signaling events and chronically promoting the breakdown of endothelial cell-cell contacts. Increasingly, our understanding of how the contributions of the placenta, immune cells, and the endothelium itself promote the endocrine milieu of PE is becoming clearer. We then describe in detail how the complex endocrine environment of PE affects endothelial cell function, why this has contributed to the difficulty in fully understanding and treating this disorder, and how a focus on signaling convergence points of many hormones may be a more successful treatment strategy.