Reply: Preeclampsia has 2 phenotypes that require different treatment strategies

The interval between the onset of increased blood pressure and proteinuria in preeclampsia and the contributing factors

PURPOSE

New-onset proteinuria, as a pivotal sign of representative renal lesions in preeclampsia, is still the most common diagnostic tool for this condition and has been proven to be related to a significantly abnormal sFlt-1/VEGF ratio in circulation. At the same time, blood pressure control plays a vital role in the occurrence and evolution of proteinuria. Therefore, it is particularly helpful to investigate their interval, not only for performing urinalysis for protein more accurately but also for evaluating blood pressure as well as the aggravation of illness, as the related research is limited.

METHODS

This retrospective study included 515 preeclampsia patients and 358 normotensive pregnant women who labored in the Second Hospital of Tianjin Medical University from January 2016 to January 2020. First, we described the onset circumstance of high blood pressure and proteinuria as well as the interval among the case group and the subgroups. Then, we determined whether there were significant differences in the basic information, laboratory test results, and newborns between the case and normal groups. Finally, multifactor ANOVA was used to determine the factors influencing the interval.

RESULTS

1. The two most common complications in preeclampsia were proteinuria (88.35%) and placental dysfunction (5.05%). Moreover, 72.04% of preeclampsia cases were diagnosed by abnormal blood pressure together with new-onset proteinuria. 2. The average interval between high blood pressure and proteinuria was 22 gestational days (from 0 to 106 days), and this interval was not significantly different between mild and severe PE (26 days vs. 21 days, P > 0.05) but significantly differed between early-onset and late-onset PE (9 days vs. 28 days, P < 0.05). 3. The number of prenatal visits, serum creatinine in the early trimester, gestational time and diastolic blood pressure value when increased blood pressure was initially detected may influence the interval between the onset of increased blood pressure and proteinuria.

CONCLUSION

New-onset proteinuria was still the main parameter for identifying preeclampsia. The interval between increased blood pressure and proteinuria was probably related to the imbalance in the sFlt-1/VEGF ratio; therefore, we should pay attention to monitor proteinuria during the prenatal visits, especially for patients with a lower frequency of prenatal visits, higher serum creatinine in the early trimester, earlier onset and higher diastolic blood pressure at the initial onset of increased blood pressure.

Noninvasive preeclampsia prediction using plasma cell-free RNA signatures

BACKGROUND

Preeclampsia, especially preterm preeclampsia and early-onset preeclampsia, is a life-threating pregnancy disorder, and the heterogeneity and complexity of preeclampsia make it difficult to predict risk and to develop treatments. Plasma cell-free RNA carries unique information from human tissue and may be useful for noninvasive monitoring of maternal, placental, and fetal dynamics during pregnancy.

OBJECTIVE

This study aimed to investigate various RNA biotypes associated with preeclampsia in plasma and to develop classifiers to predict preterm preeclampsia and early-onset preeclampsia before diagnosis.

STUDY DESIGN

We performed a novel, cell-free RNA sequencing method termed polyadenylation ligation-mediated sequencing to investigate the cell-free RNA characteristics of 715 healthy pregnancies and 202 pregnancies affected by preeclampsia before symptom onset. We explored differences in the abundance of different RNA biotypes in plasma between healthy and preeclampsia samples and built preterm preeclampsia and early-onset preeclampsia prediction classifiers using machine learning methods. Furthermore, we validated the performance of the classifiers using the external and internal validation cohorts and assessed the area under the curve and positive predictive value.

RESULTS

We detected 77 genes, including messenger RNA (44%) and microRNA (26%), that were differentially expressed in healthy mothers and mothers with preterm preeclampsia before symptom onset, which could separate participants with preterm preeclampsia from healthy samples and that played critical functional roles in preeclampsia physiology. We developed 2 classifiers for predicting preterm preeclampsia and early-onset preeclampsia before diagnosis based on 13 cell-free RNA signatures and 2 clinical features (in vitro fertilization and mean arterial pressure), respectively. Notably, both classifiers showed enhanced performance when compared with the existing methods. The preterm preeclampsia prediction model achieved 81% area under the curve and 68% positive predictive value in an independent validation cohort (preterm, n=46; control, n=151); the early-onset preeclampsia prediction model had an area under the curve of 88% and a positive predictive value of 73% in an external validation cohort (early-onset preeclampsia, n=28; control, n=234). Furthermore, we demonstrated that downregulation of microRNAs may play vital roles in preeclampsia through the upregulation of preeclampsia-relevant target genes.

CONCLUSION

In this cohort study, a comprehensive transcriptomic landscape of different RNA biotypes in preeclampsia was presented and 2 advanced classifiers with substantial clinical importance for preterm preeclampsia and early-onset preeclampsia prediction before symptom onset were developed. We demonstrated that messenger RNA, microRNA, and long noncoding RNA can simultaneously serve as potential biomarkers of preeclampsia, holding the promise of prevention of preeclampsia in the future. Abnormal cell-free messenger RNA, microRNA, and long noncoding RNA molecular changes may help to elucidate the pathogenic determinants of preeclampsia and open new therapeutic windows to effectively reduce pregnancy complications and fetal morbidity.

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.

Non-invasive Maternal Hemodynamic Assessment to Classify High-Risk Pregnancies Complicated by Fetal Growth Restriction

Objectives

To verify whether the use of the temporal criterion of 32 weeks’ gestation is effective in identifying maternal hemodynamic differences between early- and late-onset fetal growth restriction (FGR), and to test the statistical performance of a classificatory algorithm for FGR.

Materials and methods

A prospective multicenter study conducted at three centers over 17 months. Singleton pregnant women with a diagnosis of FGR based on the international Delphi survey consensus at ≥ 20 weeks of gestation were included. FGR was classified as early-onset if diagnosed &lt;32 weeks’ gestation and as late-onset if ≥32 weeks. Hemodynamic assessment was performed by USCOM-1A at the time of FGR diagnosis. Comparisons between early- and late-onset FGR among the entire study cohort, FGR associated with hypertensive disorders of pregnancy (HDP-FGR), and isolated FGR (i-FGR) were performed. In addition, HDP-FGR cases were compared to i-FGR, regardless of the temporal cut-off of 32 weeks’ gestation. Finally, a classificatory analysis based on the Random Forest model was performed to identify significant variables with the ability to differentiate FGR phenotypes.

Results

During the study period, 146 pregnant women fulfilled the inclusion criteria. In 44 cases, FGR was not confirmed at birth, thus limiting the final study population to 102 patients. In 49 (48.1%) women, FGR was associated to HDP. Fifty-nine (57.8%) cases were classified as early-onset. Comparison of the maternal hemodynamics between early- and late-onset FGR did not show any difference. Similarly, non-significant findings were observed in sensitivity analyses performed for HDP-FGR and for i-FGR. In turn, comparison between pregnant women with FGR and hypertension and women with i-FGR, independently of the gestational age at FGR diagnosis, revealed substantial differences, with the former showing higher vascular peripheral resistances and lower cardiac output, among other significant parameters. The classificatory analysis identified both phenotypic and hemodynamic variables as relevant in distinguishing HDP-FGR from i-FGR (p=0.009).

Conclusions

Our data show that HDP, rather than gestational age at FGR diagnosis, allows to appreciate specific maternal hemodynamic patterns and to accurately distinguish two different FGR phenotypes. In addition, maternal hemodynamics, alongside phenotypic characteristics, play a central role in classifying these high-risk pregnancies.