Early second-trimester plasma levels of NT-proBNP in women who subsequently develop early-onset preeclampsia

N-terminal prohormone of brain natriuretic peptide in gestational hypertension and preeclampsia - State of the art

N-terminal prohormone of brain natriuretic peptide (NT-proBNP) is a non-active prohormone secreted by ventricular cardiomyocytes into the circulation in response to ventricle overload, mainly due to increased blood volume. The changes in NT-proBNP levels during pregnancy have been investigated in multiple studies. In the case of hypertensive disorders of pregnancy, increased vasoconstriction leads to increased blood pressure and afterload. Together with the volume overload of pregnancy, it leads to higher NT-proBNP secretion. As hypertensive disorders of pregnancy are among the leading causes of prematurity and perinatal mortality, early prediction and diagnosis of gestational hypertension, and preeclampsia are essential for improving maternal and infant prognosis. NT-proBNP has been regarded as a potential biomarker of hypertensive disorders of pregnancy. In this review, we have thoroughly summarized the current data on the prognostic and diagnostic utility of NT-proBNP in patients with gestational hypertension and preeclampsia. NT-proBNP values may help distinguish between non-preeclamptic and preeclamptic patients, even if there are no significant differences in blood pressure. Moreover, in pregnancies complicated by preeclampsia, the value of increased NT-proBNP level is related to the stage and the severity of the disease. Further improvement of our knowledge about NT-proBNP as a diagnostic biomarker and a putative predictor of adverse cardiac events in women with hypertensive disorders of pregnancy should lead to better management of these patients.

Novel Associations Between Mid-Pregnancy Cardiovascular Biomarkers and Preeclampsia: An Explorative Nested Case-Control Study

Prediction of women at high risk of preeclampsia is important for prevention and increased surveillance of the disease. Current prediction models need improvement, particularly with regard to late-onset preeclampsia. Preeclampsia shares pathophysiological entities with cardiovascular disease; thus, cardiovascular biomarkers may contribute to improving prediction models. In this nested case-control study, we explored the predictive importance of mid-pregnancy cardiovascular biomarkers for subsequent preeclampsia. We included healthy women with singleton pregnancies who had donated blood in mid-pregnancy (~ 18 weeks' gestation). Cases were women with subsequent preeclampsia (n = 296, 10% of whom had early-onset preeclampsia [< 34 weeks]). Controls were women who had healthy pregnancies (n = 333). We collected data on maternal, pregnancy, and infant characteristics from medical records. We used the Olink cardiovascular II panel immunoassay to measure 92 biomarkers in the mid-pregnancy plasma samples. The Boruta algorithm was used to determine the predictive importance of the investigated biomarkers and first-trimester pregnancy characteristics for the development of preeclampsia. The following biomarkers had confirmed associations with early-onset preeclampsia (in descending order of importance): placental growth factor (PlGF), matrix metalloproteinase (MMP-12), lectin-like oxidized LDL receptor 1, carcinoembryonic antigen-related cell adhesion molecule 8, serine protease 27, pro-interleukin-16, and poly (ADP-ribose) polymerase 1. The biomarkers that were associated with late-onset preeclampsia were BNP, MMP-12, alpha-L-iduronidase (IDUA), PlGF, low-affinity immunoglobulin gamma Fc region receptor II-b, and T cell surface glycoprotein. Our results suggest that MMP-12 is a promising novel preeclampsia biomarker. Moreover, BNP and IDUA may be of value in enhancing prediction of late-onset preeclampsia.

Genetic Associations of Circulating Cardiovascular Proteins With Gestational Hypertension and Preeclampsia

Importance

Hypertensive disorders of pregnancy (HDPs), including gestational hypertension and preeclampsia, are important contributors to maternal morbidity and mortality worldwide. In addition, women with HDPs face an elevated long-term risk of cardiovascular disease.

Objective

To identify proteins in the circulation associated with HDPs.

Design, Setting, and Participants

Two-sample mendelian randomization (MR) tested the associations of genetic instruments for cardiovascular disease-related proteins with gestational hypertension and preeclampsia. In downstream analyses, a systematic review of observational data was conducted to evaluate the identified proteins' dynamics across gestation in hypertensive vs normotensive pregnancies, and phenome-wide MR analyses were performed to identify potential non-HDP-related effects associated with the prioritized proteins. Genetic association data for cardiovascular disease-related proteins were obtained from the Systematic and Combined Analysis of Olink Proteins (SCALLOP) consortium. Genetic association data for the HDPs were obtained from recent European-ancestry genome-wide association study meta-analyses for gestational hypertension and preeclampsia. Study data were analyzed October 2022 to October 2023.

Exposures

Genetic instruments for 90 candidate proteins implicated in cardiovascular diseases, constructed using cis-protein quantitative trait loci (cis-pQTLs).

Main Outcomes and Measures

Gestational hypertension and preeclampsia.

Results

Genetic association data for cardiovascular disease-related proteins were obtained from 21 758 participants from the SCALLOP consortium. Genetic association data for the HDPs were obtained from 393 238 female individuals (8636 cases and 384 602 controls) for gestational hypertension and 606 903 female individuals (16 032 cases and 590 871 controls) for preeclampsia. Seventy-five of 90 proteins (83.3%) had at least 1 valid cis-pQTL. Of those, 10 proteins (13.3%) were significantly associated with HDPs. Four were robust to sensitivity analyses for gestational hypertension (cluster of differentiation 40, eosinophil cationic protein [ECP], galectin 3, N-terminal pro-brain natriuretic peptide [NT-proBNP]), and 2 were robust for preeclampsia (cystatin B, heat shock protein 27 [HSP27]). Consistent with the MR findings, observational data revealed that lower NT-proBNP (0.76- to 0.88-fold difference vs no HDPs) and higher HSP27 (2.40-fold difference vs no HDPs) levels during the first trimester of pregnancy were associated with increased risk of HDPs, as were higher levels of ECP (1.60-fold difference vs no HDPs). Phenome-wide MR analyses identified 37 unique non-HDP-related protein-disease associations, suggesting potential on-target effects associated with interventions lowering HDP risk through the identified proteins.

Conclusions and Relevance

Study findings suggest genetic associations of 4 cardiovascular disease-related proteins with gestational hypertension and 2 associated with preeclampsia. Future studies are required to test the efficacy of targeting the corresponding pathways to reduce HDP risk.

Independent predictors of preeclampsia and their impact on the complication in Bulgarian study group of pregnant women

INTRODUCTION

One of the major obstetrical complications, affecting 2%-8% of all pregnancies, is preeclampsia. To predict the onset of preeclampsia, several methods have recently been put forth. The Fetal Medicine Foundation has developed combined screening that can identify the vast majority of women who will develop preeclampsia using a combination of maternal factors, obstetrical history, biochemical, and biophysical factors.

The Utilization and Interpretation of Cardiac Biomarkers During Pregnancy: JACC: Advances Expert Panel

Cardiac biomarkers are widely used in the nonpregnant population when acute cardiovascular (CV) pathology is suspected; however, the behavior of these biomarkers in the context of pregnancy is less well understood. Pregnant individuals often have symptoms that mimic those of cardiac dysfunction, and complications of pregnancy may include CV disease. This paper will summarize our current knowledge on the use of cardiac biomarkers in pregnancy and provide suggestions on how to use these tools in clinical practice based on the available evidence. Natriuretic peptides and troponin should not be measured routinely in uncomplicated pregnancy, where values should remain low as in the nonpregnant population. In the context of pre-existing or suspected CV disease, these biomarkers retain their negative predictive value. Elevations of both natriuretic peptides and troponin may occur without clear clinical significance in the immediate postpartum period. Elevations of these markers should always prompt further investigation into possible CV pathology.

First trimester preeclampsia screening and prediction

Preeclampsia is a major cause of maternal and perinatal morbidity and mortality. Early-onset disease requiring preterm delivery is associated with a higher risk of complications in both mothers and babies. Evidence suggests that the administration of low-dose aspirin initiated before 16 weeks' gestation significantly reduces the rate of preterm preeclampsia. Therefore, it is important to identify pregnant women at risk of developing preeclampsia during the first trimester of pregnancy, thus allowing timely therapeutic intervention. Several professional organizations such as the American College of Obstetricians and Gynecologists (ACOG) and National Institute for Health and Care Excellence (NICE) have proposed screening for preeclampsia based on maternal risk factors. The approach recommended by ACOG and NICE essentially treats each risk factor as a separate screening test with additive detection rate and screen-positive rate. Evidence has shown that preeclampsia screening based on the NICE and ACOG approach has suboptimal performance, as the NICE recommendation only achieves detection rates of 41% and 34%, with a 10% false-positive rate, for preterm and term preeclampsia, respectively. Screening based on the 2013 ACOG recommendation can only achieve detection rates of 5% and 2% for preterm and term preeclampsia, respectively, with a 0.2% false-positive rate. Various first trimester prediction models have been developed. Most of them have not undergone or failed external validation. However, it is worthy of note that the Fetal Medicine Foundation (FMF) first trimester prediction model (namely the triple test), which consists of a combination of maternal factors and measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has undergone successful internal and external validation. The FMF triple test has detection rates of 90% and 75% for the prediction of early and preterm preeclampsia, respectively, with a 10% false-positive rate. Such performance of screening is superior to that of the traditional method by maternal risk factors alone. The use of the FMF prediction model, followed by the administration of low-dose aspirin, has been shown to reduce the rate of preterm preeclampsia by 62%. The number needed to screen to prevent 1 case of preterm preeclampsia by the FMF triple test is 250. The key to maintaining optimal screening performance is to establish standardized protocols for biomarker measurements and regular biomarker quality assessment, as inaccurate measurement can affect screening performance. Tools frequently used to assess quality control include the cumulative sum and target plot. Cumulative sum is a sensitive method to detect small shifts over time, and point of shift can be easily identified. Target plot is a tool to evaluate deviation from the expected multiple of median and the expected median of standard deviation. Target plot is easy to interpret and visualize. However, it is insensitive to detecting small deviations. Adherence to well-defined protocols for the measurements of mean arterial pressure, uterine artery pulsatility index, and placental growth factor is required. This article summarizes the existing literature on the different methods, recommendations by professional organizations, quality assessment of different components of risk assessment, and clinical implementation of the first trimester screening for preeclampsia.

A machine-learning-based algorithm improves prediction of preeclampsia-associated adverse outcomes

BACKGROUND

Preeclampsia presents a highly prevalent burden on pregnant women with an estimated incidence of 2% to 5%. Preeclampsia increases the maternal risk of death 20-fold and is one of the main causes of perinatal morbidity and mortality. Novel biomarkers, such as soluble fms-like tyrosine kinase-1 and placental growth factor in addition to a wide span of conventional clinical data (medical history, physical symptoms, laboratory parameters, etc.), present an excellent basis for the application of early-detection machine-learning models.

OBJECTIVE

This study aimed to develop, train, and test an automated machine-learning model for the prediction of adverse outcomes in patients with suspected preeclampsia.

STUDY DESIGN

Our real-world dataset of 1647 (2472 samples) women was retrospectively recruited from women who presented to the Department of Obstetrics at the Charité - Universitätsmedizin Berlin, Berlin, Germany, between July 2010 and March 2019. After standardization and data cleaning, we calculated additional features regarding the biomarkers soluble fms-like tyrosine kinase-1 and placental growth factor and sonography data (umbilical artery pulsatility index, middle cerebral artery pulsatility index, mean uterine artery pulsatility index), resulting in a total of 114 features. The target metric was the occurrence of adverse outcomes throughout the remaining pregnancy and 2 weeks after delivery. We trained 2 different models, a gradient-boosted tree and a random forest classifier. Hyperparameter training was performed using a grid search approach. All results were evaluated via a 10 × 10-fold cross-validation regimen.

RESULTS

We obtained metrics for the 2 naive machine-learning models. A gradient-boosted tree model was performed with a positive predictive value of 88%±6%, a negative predictive value of 89%±3%, a sensitivity of 66%±5%, a specificity of 97%±2%, an overall accuracy of 89%±3%, an area under the receiver operating characteristic curve of 0.82±0.03, an F1 score of 0.76±0.04, and a threat score of 0.61±0.05. The random forest classifier returned an equal positive predictive value (88%±6%) and specificity (97%±1%) while performing slightly inferior on the other available metrics. Applying differential cutoffs instead of a naive cutoff for positive prediction at ≥0.5 for the classifier's results yielded additional increases in performance.

CONCLUSION

Machine-learning techniques were a valid approach to improve the prediction of adverse outcomes in pregnant women at high risk of preeclampsia vs current clinical standard techniques. Furthermore, we presented an automated system that did not rely on manual tuning or adjustments.

Pro-BNP Levels and Its Prognostic Role in Chronic Hypertensive Pregnancies: A Prospective Case-Control Study From A Tertiary Care Hospital

BACKGROUND

This study aimed to investigate the prognostic value of N-terminal B-type natriuretic peptide (NT-proBNP) in pregnancies with isolated chronic hypertension (HT).

METHOD

34 pregnant women with chronic HT and 40normotensive controls were enrolled. The association between plasma NT-proBNP levels obtained in the first trimester and perinatal complications were evaluated.

RESULTS

NT-proBNP levelsstrongly predicted low birth weight (AUC=0.842, p<0.001). NT-proBNP and birth weight were negatively correlated (r= -0.323, p=0.005). NT-proBNP was found to be an individual determinant of low birth weight in univariate analysis (OR:1.03; 95%CI:1.01-1.04).

CONCLUSION

NT-proBNP levels can be useful to predict low birth weight in pregnancies with chronic HT.

Pregnant alpha-1-microglobulin (A1M) knockout mice exhibit features of kidney and placental damage, hemodynamic changes and intrauterine growth restriction

Alpha-1-microglobulin (A1M) is an antioxidant previously shown to be elevated in maternal blood during pregnancies complicated by preeclampsia and suggested to be important in the endogenous defense against oxidative stress. A knockout mouse model of A1M (A1Mko) was used in the present study to assess the importance of A1M during pregnancy in relation to the kidney, heart and placenta function. Systolic blood pressure (SBP) and heart rate (HR) were determined before and throughout gestation. The morphology of the organs was assessed by both light and electron microscopy. Gene expression profiles relating to vascular tone and oxidative stress were analyzed using RT-qPCR with validation of selected gene expression relating to vascular tone and oxidative stress response. Pregnant age-matched wild type mice were used as controls. In the A1Mko mice there was a significantly higher SBP before pregnancy that during pregnancy was significantly reduced compared to the control. In addition, the HR was higher both before and during pregnancy compared to the controls. Renal morphological abnormalities were more frequent in the A1Mko mice, and the gene expression profiles in the kidney and the heart showed downregulation of transcripts associated with vasodilation. Simultaneously, an upregulation of vasoconstrictors, blood pressure regulators, and genes for osmotic stress response, ion transport and reactive oxygen species (ROS) metabolism occurred. Fetal weight was lower in the A1Mko mice at E17.5. The vessels in the labyrinth zone of the placentas and the endoplasmic reticulum in the spongiotrophoblasts were collapsed. The gene profiles in the placenta showed downregulation of antioxidants, ROS metabolism and oxidative stress response genes. In conclusion, intact A1M expression is necessary for the maintenance of normal kidney, heart as well as placental structure and function for a normal pregnancy adaptation.

Relevance of the assessment of natriuretic peptide plasma concentrations in hypertensive pregnant women

Assessment of the plasma concentrations of natriuretic peptides (NPs) is widely used to diagnose and evaluate the progression of cardiac failure, and their potential as markers of preeclampsia (PE) has been examined in recent years. It has been established that plasma concentrations of NPs do not change in the course of normal pregnancy. However, elevated levels of these peptides may have a prognostic value in patients with PE. This study presents information about the relevance of NPs assessment in the evaluation of physiological pregnancy, as well as in pregnancy complicated with arterial hypertension. The most commonly examined NPs is the N-terminal fragment of the brain natriuretic peptide (NT-proBNP), and it may be prognostic marker of PE and other complications of pregnancy.

NT-proBNP: When is it useful in Obstetric Medicine?

Pregnancy, viewed as a stress test of the haemodynamic system, may unmask underlying cardiac disease. Pregnancy may also induce de novo cardiac disease. N-terminal pro brain-type natriuretic peptide (NT-proBNP) is a useful biomarker in all clinical conditions in which the ventricle is stressed and especially stretched in the general population. In hypertensive diseases of pregnancy, increased levels of NT-proBNP in preeclampsia are associated with increased cardiac filling pressures and diastolic dysfunction. Increased levels of NT-proBNP in pregnant women with known cardiac disease may lead to earlier diagnosis of impending heart failure. Similarly, elevated levels of NT-proBNP assist with the diagnosis of peripartum cardiomyopathy and are increasingly used in follow-up. Women with known congenital heart disease who are pregnant can be screened for risk of cardiac events such as heart failure by the use of NT-proBNP levels. There is a paucity of data in pregnancy with the use of NT-proBNP and more research is needed.

The Role of Cardiac Biomarkers in Pregnancy

OPINION STATEMENT

Cardiovascular disease (CVD) is the leading cause of pregnancy-associated mortality, with an increasingly complex pregnant population. While our understanding of CVD in pregnancy continues to evolve, there remains a need to develop widely accessible tools to follow pregnant women both with and without preexisting disease with respect to cardiovascular risk, particularly for those presenting with symptoms suggestive of cardiovascular pathology. Thus, research is emerging with respect to the potential role of novel and established cardiac biomarkers in diagnosing and following CVD in pregnancy. Here, we review the normal hemodynamics of pregnancy and the behavior of various biomarkers in both normal and complicated pregnancies.