The prediction of late-onset preeclampsia: Results from a longitudinal proteomics study

Protein biomarker signatures of preeclampsia - a longitudinal 5000-multiplex proteomics study

We aimed to explore novel biomarker candidates and biomarker signatures of late-onset preeclampsia (LOPE) by profiling samples collected in a longitudinal discovery cohort with a high-throughput proteomics platform. Using the Somalogic 5000-plex platform, we analyzed proteins in plasma samples collected at three visits (gestational weeks (GW) 12-19, 20-26 and 28-34 in 35 women with LOPE (birth ≥ 34 GW) and 70 healthy pregnant women). To identify biomarker signatures, we combined Elastic Net with Stability Selection for stable variable selection and validated their predictive performance in a validation cohort. The biomarker signature with the highest predictive performance (AUC 0.88 (95% CI 0.85-0.97)) was identified in the last trimester of pregnancy (GW 28-34) and included the Fatty acid amid hydrolase 2 (FAAH2), HtrA serine peptidase 1 (HTRA1) and Interleukin-17 receptor C (IL17RC) together with sFLT1 and maternal age, BMI and nulliparity. Our biomarker signature showed increased or similar predictive performance to the sFLT1/PGF-ratio within our data set, and we were able to validate the biomarker signature in a validation cohort (AUC ≥ 0.90). Further validation of these candidates should be performed using another protein quantification platform in an independent cohort where the negative and positive predictive values can be validly calculated.

Proteomic Profiles of Maternal Plasma Extracellular Vesicles for Prediction of Preeclampsia

PROBLEM

Preeclampsia is a heterogeneous syndrome of diverse etiologies and molecular pathways leading to distinct clinical subtypes. Herein, we aimed to characterize the extracellular vesicle (EV)-associated and soluble fractions of the maternal plasma proteome in patients with preeclampsia and to assess their value for disease prediction.

METHOD OF STUDY

This case-control study included 24 women with term preeclampsia, 23 women with preterm preeclampsia, and 94 healthy pregnant controls. Blood samples were collected from cases on average 7 weeks before the diagnosis of preeclampsia and were matched to control samples. Soluble and EV fractions were separated from maternal plasma; EVs were confirmed by cryo-EM, NanoSight, and flow cytometry; and 82 proteins were analyzed with bead-based, multiplexed immunoassays. Quantile regression analysis and random forest models were implemented to evaluate protein concentration differences and their predictive accuracy. Preeclampsia subgroups defined by molecular profiles were identified by hierarchical cluster analysis. Significance was set at p < 0.05 or false discovery rate-adjusted q < 0.1.

RESULTS

In preterm preeclampsia, PlGF, PTX3, and VEGFR-1 displayed differential abundance in both soluble and EV fractions, whereas angiogenin, CD40L, endoglin, galectin-1, IL-27, CCL19, and TIMP1 were changed only in the soluble fraction (q < 0.1). The direction of changes in the EV fraction was consistent with that in the soluble fraction for nine proteins. In term preeclampsia, CCL3 had increased abundance in both fractions (q < 0.1). The combined EV and soluble fraction proteomic profiles predicted preterm and term preeclampsia with an AUC of 78% (95% CI, 66%-90%) and 68% (95% CI, 56%-80%), respectively. Three clusters of preeclampsia featuring distinct clinical characteristics and placental pathology were identified based on combined protein data.

CONCLUSIONS

Our findings reveal distinct alterations of the maternal EV-associated and soluble plasma proteome in preterm and term preeclampsia and identify molecular subgroups of patients with distinct clinical and placental histopathologic features.

Persistent hypertension among postpartum women with comorbid HIV and preeclampsia in Zambia

BACKGROUND

Persistent hypertension is common after preeclampsia and is causally tied to later cardiovascular risks. This study examined whether being HIV-infected and on antiretroviral therapy (ART) is associated with persistent postpartum hypertension among women diagnosed with preeclampsia.

METHODS

We conducted a six-month prospective cohort study at Kanyama and Women and Newborn hospitals from January 01, 2022, to June 30, 2023, among 190 women diagnosed with preeclampsia (59 HIV-positive, 131 HIV-negative). Sociodemographic and clinical characteristics were collected at delivery, six weeks, three months and six months after giving birth. Persistent hypertension was diagnosed if a participant presented with elevated blood pressure ≥140mmHg and/or diastolic blood pressure ≥90mmHg and/or taking medication for hypertension at the study visit. We used a generalized estimating equation to describe the relationship between treated HIV and persistent hypertension six months following delivery.

RESULTS

We retained 136 participants (71.6%) to six months postpartum, at a median age of 30 years. Overall, persistent hypertension at six weeks, three months, and six months postpartum was common (37.4%, 17.1% and 16.9%, respectively). Six-week postpartum prevalence was higher in the HIV group than HIV-negative group (54.6% vs 28.8%, p<0.001), with no measurable difference at three months (24.3% vs 13.2%, p = 0.145) or six months (18.2% vs 16.3%, p = 0.787). Multivariable analysis demonstrates higher odds (adjusted odds ratio [aOR] = 1.68, 95% CI: 1.09-2.60) of persistent hypertension among the HIV+treatment group than HIV-negative counterparts after accounting for age, body mass index and time since delivery.

CONCLUSION

We demonstrate an elevated risk of persistent hypertension among postpartum women with comorbid preeclampsia and treated HIV. Peripartum patients in HIV-endemic settings may benefit from timely detection of hypertension and treatment interventions to improve health outcomes.

Large-Scale Proteomics in Early Pregnancy and Hypertensive Disorders of Pregnancy

Importance

There is no consensus regarding the best method for prediction of hypertensive disorders of pregnancy (HDP), including gestational hypertension and preeclampsia.

Objective

To determine predictive ability in early pregnancy of large-scale proteomics for prediction of HDP.

Design, Setting, and Participants

This was a nested case-control study, conducted in 2022 to 2023, using clinical data and plasma samples collected between 2010 and 2013 during the first trimester, with follow-up until pregnancy outcome. This multicenter observational study took place at 8 academic medical centers in the US. Nulliparous individuals during first-trimester clinical visits were included. Participants with HDP were selected as cases; controls were selected from those who delivered at or after 37 weeks without any HDP, preterm birth, or small-for-gestational-age infant. Age, self-reported race and ethnicity, body mass index, diabetes, health insurance, and fetal sex were available covariates.

Exposures

Proteomics using an aptamer-based assay that included 6481 unique human proteins was performed on stored plasma. Covariates were used in predictive models.

Main Outcomes and Measures

Prediction models were developed using the elastic net, and analyses were performed on a randomly partitioned training dataset comprising 80% of study participants, with the remaining 20% used as an independent testing dataset. Primary measure of predictive performance was area under the receiver operating characteristic curve (AUC).

Results

This study included 753 HDP cases and 1097 controls with a mean (SD) age of 26.9 (5.5) years. Maternal race and ethnicity were 51 Asian (2.8%), 275 non-Hispanic Black (14.9%), 275 Hispanic (14.9%), 1161 non-Hispanic White (62.8% ), and 88 recorded as other (4.8%), which included those who did not identify according to these designations. The elastic net model, allowing for forced inclusion of prespecified covariates, was used to adjust protein-based models for clinical and demographic variables. Under this approach, no proteins were selected to augment the clinical and demographic covariates. The predictive performance of the resulting model was modest, with a training set AUC of 0.64 (95% CI, 0.61-0.67) and a test set AUC of 0.62 (95% CI, 0.56-0.68). Further adjustment for study site yielded only minimal changes in AUCs.

Conclusions and Relevance

In this case-control study with detailed clinical data and stored plasma samples available in the first trimester, an aptamer-based proteomics panel did not meaningfully add to predictive utility over and above clinical and demographic factors that are routinely available.

Longitudinal Assessment of Oxidative Stress Markers in Women with Preeclampsia

Preeclampsia (PE) is a pregnancy-specific disorder and a major contributor to maternal and fetal morbidity and mortality. Role of oxidative stress in early pregnancy with the pathophysiology of the disorder is unclear. The current study aims to analyse maternal levels of oxidative stress markers (MDA and protein carbonyl) longitudinally across gestation and placental levels of oxidative stress markers (MDA, protein carbonyl and 8-oxo-2'-deoxyguanosine) in women with PE and compare them with non-PE women. 324 pregnant women (216 non-PE and 108 PE women) were longitudinally followed during pregnancy. Women with preeclampsia were stratified as early onset preeclampsia (EOP) and late onset preeclampsia (LOP) Maternal blood at four time points across gestation (11-14 weeks, 18-22 weeks, 26-28 weeks, and at delivery) and placenta were collected. Maternal and placental levels of oxidative stress markers were assessed using commercially available kits. Maternal plasma MDA and protein carbonyl levels were comparable between the PE and non-PE group at all timepoints across gestation. Maternal plasma MDA were significantly higher levels at 26-28 weeks in EOP women when compared to non-PE women (p < 0.05). Placental 8-oxo-dG levels were lower in the EOP group as compared to non-PE (p < 0.05). Elevated plasma MDA levels were positively associated with birth length at 18-22 weeks and 26-28 weeks in the PE group (p < 0.05 for both). Maternal plasma MDA levels were positively associated with systolic blood pressure at 18-22 weeks. Oxidative stress in early pregnancy is not associated with risk of PE.

Different Proteomic Profiles Regarding Antihypertensive Therapy in Preeclampsia Pregnant

Preeclampsia (PE) is a hypertensive pregnancy syndrome associated with target organ damage and increased cardiovascular risks, necessitating antihypertensive therapy. However, approximately 40% of patients are nonresponsive to treatment, which results in worse clinical outcomes. This study aimed to compare circulating proteomic profiles and identify differentially expressed proteins among 10 responsive (R-PE), 10 nonresponsive (NR-PE) patients, and 10 healthy pregnant controls (HP). We also explored correlations between these proteins and clinical data. Plasma protein relative quantification was performed using mass spectrometry, followed by bioinformatics analyses with the UniProt database, PatternLab for Proteomics 4.0, and MetaboAnalyst software (version 6.0). Considering a fold change of 1.5, four proteins were differentially expressed between NR-PE and R-PE: one upregulated (fibronectin) and three downregulated (pregnancy-specific beta-1-glycoprotein 1, complement C4B, and complement C4A). Between NR-PE and HP, six proteins were differentially expressed: two upregulated (clusterin and plasmin heavy chain A) and four downregulated (apolipoprotein L1, heparin cofactor II, complement C4B, and haptoglobin-related protein). Three proteins were differentially expressed between R-PE and HP: one downregulated (transthyretin) and two upregulated (apolipoprotein C1 and hemoglobin subunit beta). These findings suggest a complex interplay of these proteins involved in inflammatory, immune, and metabolic processes with antihypertensive therapy responsiveness and PE pathophysiology.

Maternal exposure to bioclimatic stress and hypertensive disorders of pregnancy in Western Australia: identifying potential critical windows of susceptibility

The anthropogenic climate change may impact pregnancy outcomes. Rather than ambient temperature, we aimed to use a composite bioclimatic metric (Universal Thermal Climate Index, UTCI) to identify critical susceptible windows for the associations between bioclimatic exposure and hypertensive disorders of pregnancy (HDPs) risk. Daily UTCI exposure from 12 weeks of preconception through pregnancy was linked to 415,091 singleton pregnancies between 1st January 2000 and 31st December 2015 in Western Australia. Adjusted weekly-specific and cumulative odds ratios (ORs) and 95% confidence intervals (CIs) of gestational hypertension and preeclampsia were estimated with distributed lag non-linear and standard non-linear logistic regressions. Exposures from early pregnancy to week 30 were associated with greater odds of HDPs with critical susceptible windows, particularly elevated at the 1st (10.2 °C) and 99th (26.0 °C) exposure centiles as compared to the median (14.2 °C). The most elevated ORs were 1.07 (95% CI 1.06, 1.08) in weeks 8-18 for gestational hypertension and 1.10 (95% CI 1.08, 1.11) in weeks 11-16 for preeclampsia for the 99th exposure centile. Cumulative exposures associated with HDPs with relatively higher but less precise ORs. The effects of high exposure to HDPs indicated sociodemographic inequalities. The identified critical periods and subpopulations could benefit from climate-related interventions.

Serum proteomics of mother-infant dyads carrying HLA-conferred type 1 diabetes risk

In-utero and dietary factors make important contributions toward health and development in early childhood. In this respect, serum proteomics of maturing infants can provide insights into studies of childhood diseases, which together with perinatal proteomes could reveal further biological perspectives. Accordingly, to determine differences between feeding groups and changes in infancy, serum proteomics analyses of mother-infant dyads with HLA-conferred susceptibility to type 1 diabetes (n = 22), weaned to either an extensively hydrolyzed or regular cow's milk formula, were made. The LC-MS/MS analyses included samples from the beginning of third trimester, the time of delivery, 3 months postpartum, cord blood, and samples from the infants at 3, 6, 9, and 12 months. Correlations between ranked protein intensities were detected within the dyads, together with perinatal and age-related changes. Comparison with intestinal permeability data revealed a number of significant correlations, which could merit further consideration in this context.

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.

10. Role of high dimensional technology in preeclampsia (omics in preeclampsia)

Preeclampsia is a pregnancy-specific disease that has no known precise cause. Integrative biology approach based on multi-omics has been applied to identify upstream pathways and better understand the pathophysiology of preeclampsia. At DNA level, genomics and epigenomics studies have revealed numerous genetic variants associated with preeclampsia, including those involved in regulating blood pressure and immune response. Transcriptomics analyses have revealed altered expression of genes in preeclampsia, particularly those related to inflammation and angiogenesis. At protein level, proteomics studies have identified potential biomarkers for preeclampsia diagnosis and prediction in addition to revealing the main pathophysiological pathways involved in this disease. At metabolite level, metabolomics has highlighted altered lipid and amino acid metabolisms in preeclampsia. Finally, microbiomics studies have identified dysbiosis in the gut and vaginal microbiota in pregnant women with preeclampsia. Overall, omics technologies have improved our understanding of the complex molecular mechanisms underlying preeclampsia. However, further research is warranted to fully integrate and translate these omics findings into clinical practice.

Classification of preeclampsia according to molecular clusters with the goal of achieving personalized prevention

The prevention of pre-eclampsia is difficult due to the syndromic nature and multiple underlying mechanisms of this severe complication of pregnancy. The current clinical distinction between early- and late-onset disease, although clinically useful, does not reflect the true nature and complexity of the pathologic processes leading to pre-eclampsia. The current gaps in knowledge on the heterogeneous molecular pathways of this syndrome and the lack of adequate, specific diagnostic methods are major obstacles to early screening and tailored preventive strategies. The development of novel diagnostic tools for detecting the activation of the identified disease pathways would enable early, accurate screening and personalized preventive therapies. We implemented a holistic approach that includes the utilization of different proteomic profiling methods of maternal plasma samples collected from various ethnic populations and the application of systems biology analysis to plasma proteomic, maternal demographic, clinical characteristic, and placental histopathologic data. This approach enabled the identification of four molecular subclasses of pre-eclampsia in which distinct and shared disease mechanisms are activated. The current review summarizes the results and conclusions from these studies and the research and clinical implications of our findings.

Penalized regression with multiple sources of prior effects

MOTIVATION

In many high-dimensional prediction or classification tasks, complementary data on the features are available, e.g. prior biological knowledge on (epi)genetic markers. Here we consider tasks with numerical prior information that provide an insight into the importance (weight) and the direction (sign) of the feature effects, e.g. regression coefficients from previous studies.

RESULTS

We propose an approach for integrating multiple sources of such prior information into penalized regression. If suitable co-data are available, this improves the predictive performance, as shown by simulation and application.

AVAILABILITY AND IMPLEMENTATION

The proposed method is implemented in the R package transreg (https://github.com/lcsb-bds/transreg, https://cran.r-project.org/package=transreg).

Diagnostic value of platelet to lymphocyte ratio in preeclampsia: a systematic review and meta-analysis

BACKGROUND

Using straightforward and accessible haematological parameters platelet/lymphocyte ratio (PLR) to diagnose preeclampsia (PE) early and precisely remains a challenge. Although several clinical studies suggested that PLR is able to diagnose PE, there has been no systematic evaluation of the diagnostic utility.

OBJECTIVES

To examine the diagnostic accuracy and potential applicability of PLR in the detection of PE.

STUDY DESIGN

Seven databases were searched using a combination of PLR and PE terms, and all potentially pertinent studies were systematically searched up to March 2023. All potentially relevant studies both prospective and retrospective were reviewed. To assess the diagnostic value of PLR for PE, pooled sensitivity (Sen), specificity (Spe), diagnostic odds ratio (DOR) and area under the summary receiver operating characteristic curve (SROC-AUC) were calculated.

RESULTS

Thirteen studies were enrolled in the meta-analysis. In the second and third trimesters, the PLR suggested a diagnostic value for PE with a pooled Sen of 54.7% [95% confidence interval (CI) (51.7, 57.6)], Spe of 77.8% [95% CI (75.5, 80.0)], + LR of 2.457 [95% CI (1.897, 3.182)], -LR of 0.584 [95% CI (0.491, 0.695)], DOR of 4.434 [95% CI (3.071, 6.402)], the SROC-AUC of 0.7296 and the standard error (SE) of 0.0370.

CONCLUSION

For the diagnosis of PE, PLR has a limited sensitivity but an acceptable specificity, and showed moderate accuracy. Further using complete blood count (CBC) indicators such as PLR alone or in combination to diagnose and predict PE could reduce healthcare costs and improve maternal and child prognosis.

The role and expression of pro/antiangiogenic factors and microRNAs in gestational hypertension and pre-eclampsia

OBJECTIVE

Pre-eclampsia and gestational hypertension are two common hypertensive disorders of pregnancy with pre-eclampsia accounting for high foetal and maternal morbidity and mortality rate. These disorders have an unknown aetiology and their hypertensive and end-organ pathophysiology may present too late in pregnancy. This makes the identification of early detection and differentiation markers vital. MicroRNAs have strongly been associated with pregnancy and their imbalance has been associated with the angiogenic dysregulation seen in pre-eclampsia. This study assesses the expression of pro- and antiangiogenic factors and their corresponding microRNAs in the maternal circulation of patients with pre-eclampsia and gestational hypertension.

STUDY DESIGN

We analyzed angiogenic factors expression (sEng, TGF-β, VEGF) normalized against housekeeping gene β-actin and microRNAs (miRs: 210, 29B, 126) normalized against miR U6, potentially associated with pre-eclampsia and gestational hypertension using the targeted qPCR technique. These analytes were examined from early-onset (<34 weeks) (EOPE) (n = 12), late-onset (>34 weeks) (LOPE) (n = 12) pre-eclampsia, gestational hypertension (GH) (n = 12) and two gestationally matched normotensive groups (NG1 and 2) (n = 12) each in South African women of African ancestry. Group comparisons of experimental vs. control groups were assessed using t-test analysis for significance and represented as fold change expression.

RESULTS

The relative expression in group comparisons showed significant (p < 0.05) fold change of VEGF, TGF-β, sEng and miR126 in the EOPE vs. NG1. The GH vs. NG1 exhibited significant changes in VEGF, TGF-β, miR126, miR210 and miR29B. The LOPE vs. NG2 showed significant relative expression in all the angiogenic factors (VEGF, TGF-β and sEng). The GH vs. NG2 showed significant expression in VEGF and miR29B. The LOPE vs. EOPE showed significant fold changes in VEGF and miR210. Finally, only the GH vs. EOPE showed significant differences in miR210 and miR29B (p < 0.05).

CONCLUSION

This study provides better insights into angiogenic factors and microRNAs specificity to the subtypes of gestational hypertensive disorders in pregnancy. Relative expression analysis of angiogenic factors and microRNAs showed possible novel characteristics of gestational hypertension, and potential common molecular and pathological profiles with pre-eclampsia. Furthermore, we postulate that sEng and miR29B could be early detection markers for pre-eclampsia and gestational hypertension, respectively.

The role of first trimester eosinophil count and eosinophil-based complete blood cell indices in the predictiction of preeclampsia: A case-control study

INTRODUCTION

The importance of eosinophils in the pathogenesis of preeclampsia is an question of interest and there are recent studies in the literature indicating significantly lower eosinophil count values in pregnant women with preeclampsia. The present study aims to evaluate the utility of first-trimester eosinophil count and eosinophil-based complete blood cell count indices in the prediction of preeclampsia.

METHODS

Pregnant women diagnosed with preeclampsia (n = 281) were retrospectively compared with a control group (n = 307). The utility of first trimester eosinophil count, neutrophil to eosinophil ratio (NER) (neutrophil/eosinophil), leukocyte to eosinophil ratio (LER) (leukocyte/eosinophil), eosinophil to monocyte ratio (EMR) (eosinophil/monocyte) and, eosinophil to lymphocyte ratio (ELR) (eosinophil/lymphocyte) in the prediction of preeclampsia were evaluated.

RESULTS

Optimal cut-off values for eosinophil count, NER, LER, EMR and, ELR in predicting preeclampsia were 0.07 (AUC: 0.62, 58.7% sensitivity, 56.4% specificity), 90.9 (AUC: 0.65, 61.1% sensitivity, 59.4% specificity), 125.7 (AUC: 0.64, 61.4% sensitivity, 58.4% specificity), 0.15 (AUC: 0.63, 60.1% sensitivity, 59.6% specificity) and, 0.03 (AUC: 0.62, 60.9% sensitivity, 57% specificity), respectively. Mentioned values in predicting early-onset preeclampsia were 0.07 (AUC: 0.64, 60.5% sensitivity, 50.8% specificity), 102.1 (AUC: 0.64, 62.4% sensitivity, 58.8% specificity), 140.2 (AUC: 0.65, 63.5% sensitivity, 59.1% soecificity), 0.14 (AUC: 0.66, 66.3% sensitivity, 59.2% specificity), and, 0.03 (AUC: 0.63, 60.5% sensitivity, 57.4% specificity), respectively. The optimal cut-off value for EMR in the prediction of preeclampsia with severe features was 0.16 (AUC: 0.56, 56.9% sensitivity, 53.2% specificity).

DISCUSSION

Eosinophil-based complete blood count indices may be used to predict early-onset preeclampsia with relatively low sensitivity and specificity.

Can single-cell and spatial omics unravel the pathophysiology of pre-eclampsia?

Pre-eclampsia is a leading cause of maternal and fetal morbidity and mortality. Characterised by the onset of hypertension and proteinuria in the second half of pregnancy, it can lead to maternal end-organ injury such as cerebral ischemia and oedema, pulmonary oedema and renal failure, and potentially fatal outcomes for both mother and fetus. The causes of the different maternal end-organ phenotypes of pre-eclampsia and why some women develop pre-eclampsia condition early in pregnancy have yet to be elucidated. Omics methods include proteomics, genomics, metabolomics, transcriptomics. These omics techniques, previously mostly used on bulk tissue and individually, are increasingly available at a single cellular level and can be combined with each other. Multi-omics techniques on a single-cell or spatial level provide us with a powerful tool to understand the pathophysiology of pre-eclampsia. This review will explore the status of omics methods and how they can and could contribute to understanding the pathophysiology of pre-eclampsia.

Erythrocyte fatty acids and desaturase indices in early pregnancy are associated with risk of preeclampsia

Preeclampsia (PE) is a pregnancy disorder that may be associated with inadequate maternal nutrition. Fatty acids are vital for placental and fetal growth. Fatty acid desaturases, key enzymes influencing the metabolism of polyunsaturated fatty acids, are reported to be associated with cardiometabolic risk. Any imbalance in the levels of omega-3 and omega-6 fatty acids can result in increased inflammatory response. The current study reports the levels of erythrocyte fatty acids and desaturase index across gestation in women who develop PE (n = 108) and compares them with non-PE women (n = 216). Maternal erythrocyte fatty acids were measured at 4 time points during pregnancy (i.e., 11-14, 18-22, 26-28 weeks and at delivery) using gas chromatography. Maternal total erythrocyte saturated fatty acids and omega-6/omega-3 fatty acid ratio was higher in the PE group as compared to the non-PE group at 11-14 weeks and 18-22 weeks respectively. Maternal Δ5 desaturase index was lower while Δ6 desaturase index was higher in the PE group at 11-14 and 18-22 weeks. Maternal stearoyl CoA desaturase-18 (SCD-18) index was lower at 11-14 weeks and at delivery. These changes were mainly observed in the early onset PE (EOP) group. Δ6 desaturase index at 11-14 weeks predicted the risk of EOP. Imbalance in fatty acid levels and desaturase indices predate the clinical diagnosis of PE, indicating their role in its pathophysiology. Measurement of fatty acids and desaturase indices in early pregnancy merits evaluation as predictors of risk of PE.

Pregnancy-specific responses to COVID-19 revealed by high-throughput proteomics of human plasma

BACKGROUND

Pregnant women are at greater risk of adverse outcomes, including mortality, as well as obstetrical complications resulting from COVID-19. However, pregnancy-specific changes that underlie such worsened outcomes remain unclear.

METHODS

Plasma samples were collected from pregnant women and non-pregnant individuals (male and female) with (n = 72 pregnant, 52 non-pregnant) and without (n = 29 pregnant, 41 non-pregnant) COVID-19. COVID-19 patients were grouped as asymptomatic, mild, moderate, severe, or critically ill according to NIH classifications. Proteomic profiling of 7,288 analytes corresponding to 6,596 unique protein targets was performed using the SOMAmer platform.

RESULTS

Herein, we profile the plasma proteome of pregnant and non-pregnant COVID-19 patients and controls and show alterations that display a dose-response relationship with disease severity; yet, such proteomic perturbations are dampened during pregnancy. In both pregnant and non-pregnant state, the proteome response induced by COVID-19 shows enrichment of mediators implicated in cytokine storm, endothelial dysfunction, and angiogenesis. Shared and pregnancy-specific proteomic changes are identified: pregnant women display a tailored response that may protect the conceptus from heightened inflammation, while non-pregnant individuals display a stronger response to repel infection. Furthermore, the plasma proteome can accurately identify COVID-19 patients, even when asymptomatic or with mild symptoms.

CONCLUSION

This study represents the most comprehensive characterization of the plasma proteome of pregnant and non-pregnant COVID-19 patients. Our findings emphasize the distinct immune modulation between the non-pregnant and pregnant states, providing insight into the pathogenesis of COVID-19 as well as a potential explanation for the more severe outcomes observed in pregnant women.

The amniotic fluid proteome changes with term labor and informs biomarker discovery in maternal plasma

The intra-uterine components of labor, namely, myometrial contractility, cervical ripening, and decidua/membrane activation, have been extensively characterized and involve a local pro-inflammatory milieu of cellular and soluble immune mediators. Targeted profiling has demonstrated that such processes extend to the intra-amniotic space, yet unbiased analyses of the proteome of human amniotic fluid during labor are lacking. Herein, we utilized an aptamer-based platform to characterize 1,310 amniotic fluid proteins and found that the proteome undergoes substantial changes with term labor (251 proteins with differential abundance, q < 0.1, and fold change > 1.25). Proteins with increased abundance in labor are enriched for immune and inflammatory processes, consistent with prior reports of labor-associated changes in the intra-uterine space. By integrating the amniotic fluid proteome with previously generated placental-derived single-cell RNA-seq data, we demonstrated the labor-driven upregulation of signatures corresponding to stromal-3 and decidual cells. We also determined that changes in amniotic fluid protein abundance are reflected in the maternal plasma proteome. Collectively, these findings provide novel insights into the amniotic fluid proteome in term labor and support its potential use as a source of biomarkers to distinguish between true and false labor by using maternal blood samples.

Molecular subclasses of preeclampsia characterized by a longitudinal maternal proteomics study: distinct biomarkers, disease pathways and options for prevention

OBJECTIVES

The heterogeneous nature of preeclampsia is a major obstacle to early screening and prevention, and a molecular taxonomy of disease is needed. We have previously identified four subclasses of preeclampsia based on first-trimester plasma proteomic profiles. Herein, we expanded this approach by using a more comprehensive panel of proteins profiled in longitudinal samples.

METHODS

Proteomic data collected longitudinally from plasma samples of women who developed preeclampsia (n=109) and of controls (n=90) were available from our previous report on 1,125 proteins. Consensus clustering was performed to identify subgroups of patients with preeclampsia based on data from five gestational-age intervals by using select interval-specific features. Demographic, clinical, and proteomic differences among clusters were determined. Differentially abundant proteins were used to identify cluster-specific perturbed KEGG pathways.

RESULTS

Four molecular clusters with different clinical phenotypes were discovered by longitudinal proteomic profiling. Cluster 1 involves metabolic and prothrombotic changes with high rates of early-onset preeclampsia and small-for-gestational-age neonates; Cluster 2 includes maternal anti-fetal rejection mechanisms and recurrent preeclampsia cases; Cluster 3 is associated with extracellular matrix regulation and comprises cases of mostly mild, late-onset preeclampsia; and Cluster 4 is characterized by angiogenic imbalance and a high prevalence of early-onset disease.

CONCLUSIONS

This study is an independent validation and further refining of molecular subclasses of preeclampsia identified by a different proteomic platform and study population. The results lay the groundwork for novel diagnostic and personalized tools of prevention.

Metabolic profiling of pregnancies complicated by preeclampsia: A longitudinal study

INTRODUCTION

Preeclampsia is associated with maternal metabolic disturbances, but longitudinal studies with comprehensive metabolic profiling are lacking. We aimed to determine metabolic profiles across gestation in women who developed preeclampsia compared with women with healthy pregnancies. We also explored the respective effects of body mass index (BMI) and preeclampsia on various metabolic measures.

MATERIAL AND METHODS

We measured 91 metabolites by high-throughput nuclear magnetic resonance spectroscopy at four time points (visits) during pregnancy (weeks 14-16, 22-24, 30-32 and 36-38). Samples were taken from a Norwegian pregnancy cohort. We fitted a linear regression model for each metabolic measure to compare women who developed preeclampsia (n = 38) and healthy controls (n = 70).

RESULTS

Among women who developed preeclampsia, 92% gave birth after 34 weeks of gestation. Compared to women with healthy pregnancies, women who developed preeclampsia had higher levels of several lipid-related metabolites at visit 1, whereas fewer differences were observed at visit 2. At visit 3, the pattern from visit 1 reappeared. At visit 4 the differences were larger in most subgroups of very-low-density lipoprotein particles, the smallest high-density lipoprotein, total lipids and triglycerides. Total fatty acids were also increased, of which monounsaturated fatty acids and saturated fatty acids showed more pronounced differences. Concentration of glycine tended to be lower in pregnancies with preeclampsia until visit 3, although this was not significant after correction for multiple testing. After adjustment for age, BMI, parity and gestational weight gain, all significant differences were attenuated at visits 1 and 2. The estimates were less affected by adjustment at visits 3 and 4.

CONCLUSIONS

In early pregnancy, the metabolic differences between preeclamptic and healthy pregnancies were primarily driven by maternal BMI, probably representing the women's pre-pregnancy metabolic status. In early third trimester, several weeks before clinical manifestation, the differences were less influenced by BMI, indicating preeclampsia-specific changes. Near term, women with preeclampsia developed an atherogenic metabolic profile, including elevated total lipids, very-low-density lipoprotein, triglycerides, and total fatty acids.

Feature-weighted elastic net: using "features of features" for better prediction

In some supervised learning settings, the practitioner might have additional information on the features used for prediction. We propose a new method which leverages this additional information for better prediction. The method, which we call the feature-weighted elastic net ("fwelnet"), uses these "features of features" to adapt the relative penalties on the feature coefficients in the elastic net penalty. In our simulations, fwelnet outperforms the lasso in terms of test mean squared error and usually gives an improvement in true positive rate or false positive rate for feature selection. We also apply this method to early prediction of preeclampsia, where fwelnet outperforms the lasso in terms of 10-fold cross-validated area under the curve (0.86 vs. 0.80). We also provide a connection between fwelnet and the group lasso and suggest how fwelnet might be used for multi-task learning.

Evidence of Nitric Oxide Impairment During Hypertensive Pregnancies

Hypertensive disorders of pregnancy complicate up to 10% of pregnancies worldwide, and they can be classified into (1) gestational hypertension, (2) preeclampsia, (3) chronic hypertension and (4) chronic hypertension with preeclampsia. Nitric oxide (NO) plays an essential role in the haemodynamic adaptations observed during pregnancy. It has been shown that the nitric oxide pathway's dysfunction during pregnancy is associated with placental- and vascular-related diseases such as hypertensive disorders of pregnancy. This review aims to present a brief definition of hypertensive disorders of pregnancy and physiological maternal cardiovascular adaptations during pregnancy. We also detail how NO signalling is altered in the (a) systemic vasculature, (b) uterine artery/spiral arteries, (c) implantation and (d) placenta of hypertensive disorders during pregnancy. We conclude by summarizing the anti-hypertensive therapy of hypertensive disorders of pregnancy as a specific management strategy.

First-trimester preterm preeclampsia prediction with metabolite biomarkers: differential prediction according to maternal body mass index

BACKGROUND

Prediction of preeclampsia risk is key to informing effective maternal care. Current screening for preeclampsia at 11 to 13 weeks of gestation using maternal demographic characteristics and medical history with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor can identify approximately 75% of women who develop preterm preeclampsia with delivery at <37 weeks of gestation. Further improvements to preeclampsia screening tests will likely require integrating additional biomarkers. Recent research suggests the existence of distinct maternal risk profiles. Therefore, biomarker evaluation should account for the possibility that a biomarker only predicts preeclampsia in a specific maternal phenotype.

OBJECTIVE

This study aimed to verify metabolite biomarkers as preterm preeclampsia predictors early in pregnancy in all women and across body mass index groups.

STUDY DESIGN

Observational case-control study drawn from a large prospective study on the early prediction of pregnancy complications in women attending their routine first hospital visit at King's College Hospital, London, United Kingdom, in 2010 to 2015. Pregnant women underwent a complete first-trimester assessment, including the collection of blood samples for biobanking. In 11- to 13-week plasma samples of 2501 singleton pregnancies, the levels of preselected metabolites implicated in the prediction of pregnancy complications were analyzed using a targeted liquid chromatography-mass spectrometry method, yielding high-quality quantification data on 50 metabolites. The ratios of amino acid levels involved in arginine biosynthesis and nitric oxide synthase pathways were added to the list of biomarkers. Placental growth factor and pregnancy-associated plasma protein A were also available for all study subjects, serving as comparator risk predictors. Data on 1635 control and 106 pregnancies complicated by preterm preeclampsia were considered for this analysis, normalized using multiples of medians. Prediction analyses were performed across the following patient strata: all subjects and the body mass index classes of <25, 25 to <30, and ≥30 kg/m². Adjusted median levels were compared between cases and controls and between each body mass index class group. Odds ratios and 95% confidence intervals were calculated at the mean ±1 standard deviation to gauge clinical prediction merits.

RESULTS

The levels of 13 metabolites were associated with preterm preeclampsia in the entire study population (P<.05) with particularly significant (P<.01) associations found for 6 of them, namely, 2-hydroxy-(2/3)-methylbutyric acid, 25-hydroxyvitamin D3, 2-hydroxybutyric acid, alanine, dodecanoylcarnitine, and 1-(1Z-octadecenyl)-2-oleoyl-sn-glycero-3-phosphocholine. Fold changes in 7 amino acid ratios, all involving glutamine or ornithine, were also significantly different between cases and controls (P<.01). The predictive performance of some metabolites and ratios differed according to body mass index classification; for example, ornithine (P<.001) and several ornithine-related ratios (P<.0001 to P<.01) were only strongly associated with preterm preeclampsia in the body mass index of <25 kg/m² group, whereas dodecanoylcarnitine and 3 glutamine ratios were particularly predictive in the body mass index of ≥30 kg/m² group (P<.01).

CONCLUSION

Single metabolites and ratios of amino acids related to arginine bioavailability and nitric oxide synthase pathways were associated with preterm preeclampsia risk at 11 to 13 weeks of gestation. Differential prediction was observed according to body mass index classes, supporting the existence of distinct maternal risk profiles. Future studies in preeclampsia prediction should account for the possibility of different maternal risk profiles to improve etiologic and prognostic understanding and, ultimately, clinical utility of screening tests.

Maternal plasma proteome profiling of biomarkers and pathogenic mechanisms of early-onset and late-onset preeclampsia

Preeclampsia is still the leading cause of morbidity and mortality in pregnancy without a cure. There are two phenotypes of preeclampsia, early-onset (EOPE) and late-onset (LOPE) with poorly defined pathogenic differences. This study aimed to facilitate better understanding of the mechanisms of pathophysiology of EOPE and LOPE, and identify specific biomarkers or therapeutic targets. In this study, we conducted an untargeted, label-free quantitative proteomic analyses of plasma samples from pregnant women with EOPE (n = 17) and LOPE (n = 11), and age, BMI-matched normotensive controls (n = 18). Targeted proteomics approach was also employed to validate a subset of proteins (n = 17). In total, there were 26 and 20 differentially abundant proteins between EOPE or LOPE, and normotensive controls, respectively. A series of angiogenic and inflammatory proteins, including insulin-like growth factor-binding protein 4 (IGFBP4; EOPE: FDR = 0.0030 and LOPE: FDR = 0.00396) and inter-alpha-trypsin inhibitor heavy chain H2-4 (ITIH2-4), were significantly altered in abundance in both phenotypes. Through validation we confirmed that ITIH2 was perturbed only in LOPE (p = 0.005) whereas ITIH3 and ITIH4 were perturbed in both phenotypes (p < 0.05). Overall, lipid metabolism/transport proteins associated with atherosclerosis were highly abundant in LOPE, however, ECM proteins had a more pronounced role in EOPE. The complement cascade and binding and uptake of ligands by scavenger receptors, pathways, were associated with both EOPE and LOPE.

Human Plasma Proteome During Normal Pregnancy

The human plasma proteome is underexplored despite its potential value for monitoring health and disease. Herein, using a recently developed aptamer-based platform, we profiled 7288 proteins in 528 plasma samples from 91 normal pregnancies (Gene Expression Omnibus identifier GSE206454). The coefficient of variation was <20% for 93% of analytes (median 7%), and a cross-platform correlation for selected key angiogenic and anti-angiogenic proteins was significant. Gestational age was associated with changes in 953 proteins, including highly modulated placenta- and decidua-specific proteins, and they were enriched in biological processes including regulation of growth, angiogenesis, immunity, and inflammation. The abundance of proteins corresponding to RNAs specific to populations of cells previously described by single-cell RNA-Seq analysis of the placenta was highly modulated throughout gestation. Furthermore, machine learning-based prediction of gestational age and of time from sampling to term delivery compared favorably with transcriptomic models (mean absolute error of 2 weeks). These results suggested that the plasma proteome may provide a non-invasive readout of placental cellular dynamics and serve as a blueprint for investigating obstetrical disease.

Expression of Matrix Metalloproteinase-2,-7,-9 in Serum during Pregnancy in Patients with Pre-Eclampsia: A Prospective Study

BACKGROUND

Matrix Metalloproteinases (MMPs) have been found to have important roles in vascular pathology and may be involved in the occurrence of pre-eclampsia. In this study, the serum levels of MMP-2, -7, -9 in normal pregnant women and pre-eclampsia patients were analyzed to assess their predictive value.

METHODS

A total of 1563 pregnant women from Peking University Third Hospital, from February 2021 to October 2021, were enrolled. Serum samples were collected from patients one to three times, during the different trimesters. Among the 102 singleton pre-eclampsia patients, we collected samples from 33 patients in the first trimester (6-13 GW), 33 in the second trimester (14-28 GW), 41 in the third trimester (29-41 GW) and 28 after onset of pre-eclampsia. Samples from each trimester were collected before the onset of pre-eclampsia. Then we selected 35, 37, 43 and 25 samples from 124 healthy pregnant women by matching their age, BMI and gestational weeks, using these as the control groups. Serum levels of MMP-2, -7, -9 were detected by ELISA. The receiver operating characteristic (ROC) curve was used to evaluate their predictive value.

RESULTS

Except for the first trimester, MMP-2 and MMP-7 were significantly higher in the pre-eclampsia group (p < 0.5). Additionally, in the pre-eclampsia group, MMP-9 increased significantly in the first trimester and after the onset of pre-eclampsia but decreased significantly in the second and third trimesters (p < 0.5). The ROC curve indicated that MMP-9, MMP-2 and MMP-7 were the best indicators for predicting pre-eclampsia in the first, second and third trimesters, respectively.

CONCLUSION

Increased MMP-2 and MMP-7 levels and a decreased MMP-9 level seem to be related to the pathogenesis of pre-eclampsia and are expected to be potential predictors of pre-eclampsia.

Maternal overweight and obesity and its associated factors and outcomes in human immunodeficiency virus (HIV)-infected and HIV-uninfected black South African pregnant women

AIM

This study aimed to investigate various variables between maternal overweight and/or obesity versus normal-weight pregnant black South African women living with and without human immunodeficiency virus (HIV).

METHODS

A cross-sectional study design was employed. A total of 200 pregnant women were enrolled in the study, categorized according to body mass index (BMI) (kg/m² ) into two groups: (1) overweight/obese (≥25 kg/m² ) (n = 97); and (2) nonoverweight/nonobese (<25 kg/m² ) (n = 103), where 90 were HIV-infected and 110 were HIV-uninfected. The differences between the maternal BMI categories were assessed using Fisher's exact t-test and the χ² test. Simple and multiple logistic regression analyses were used to determine factors associated with maternal overweight and obesity.

RESULTS

Multiple logistic regression analysis showed that maternal age (odds ratio [OR]: 1.061; 95% confidence interval [CI] 1.008-1.117; p = 0.023) and gestational age (OR: 1.121; 95% CI 1.005-1.251; p = 0.041) were significantly associated with maternal overweight/obesity in both HIV-infected and HIV-uninfected. For maternal health outcomes, multiple logistic regression analysis showed that hypertensive disorders (OR: 0.273; 95% CI 0.124-0.601; p = 0.001) and anemia (OR: 2.420; 95% CI 1.283-4.563; p = 0.006) were significantly associated with maternal overweight/obesity in both HIV-infected and HIV-uninfected. The overweight/obese HIV-infected participants (OR: 0.233; 95% CI 0.075-0.717; p = 0.011) had increased odds for developing hypertensive disorders compared to HIV-uninfected overweight/obese participants (OR: 0.471; 95% CI 0.172-1.291; p = 0.143).

CONCLUSIONS

Maternal overweight/obesity in both HIV-infected and HIV-uninfected pregnant black South African women was significantly associated with maternal age, gestational age, HPT disorders, and anemia. Maternal overweight/obesity decreased the odds for anemia, but increased the odds for the development of HPT disorders, especially in the HIV-infected pregnant women.

ALASCA: An R package for longitudinal and cross-sectional analysis of multivariate data by ASCA-based methods

The increasing availability of multivariate data within biomedical research calls for appropriate statistical methods that can describe and model complex relationships between variables. The extended ANOVA simultaneous component analysis (ASCA⁺) framework combines general linear models and principal component analysis (PCA) to decompose and visualize the separate effects of experimental factors. It has recently been demonstrated how linear mixed models can be included in the framework to analyze data from longitudinal experimental designs with repeated measurements (RM-ASCA⁺). The ALASCA package for R makes the ASCA⁺ framework accessible for general use and includes multiple methods for validation and visualization. The package is especially useful for longitudinal data and the ability to easily adjust for covariates is an important strength. This paper demonstrates how the ALASCA package can be applied to gain insights into multivariate data from interventional as well as observational designs. Publicly available data sets from four studies are used to demonstrate the methods available (proteomics, metabolomics, and transcriptomics).

Toward a new taxonomy of obstetrical disease: improved performance of maternal blood biomarkers for the great obstetrical syndromes when classified according to placental pathology

BACKGROUND

The major challenge for obstetrics is the prediction and prevention of the great obstetrical syndromes. We propose that defining obstetrical diseases by the combination of clinical presentation and disease mechanisms as inferred by placental pathology will aid in the discovery of biomarkers and add specificity to those already known.

OBJECTIVE

To describe the longitudinal profile of placental growth factor (PlGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and the PlGF/sFlt-1 ratio throughout gestation, and to determine whether the association between abnormal biomarker profiles and obstetrical syndromes is strengthened by information derived from placental examination, eg, the presence or absence of placental lesions of maternal vascular malperfusion.

STUDY DESIGN

This retrospective case cohort study was based on a parent cohort of 4006 pregnant women enrolled prospectively. The case cohort of 1499 pregnant women included 1000 randomly selected patients from the parent cohort and all additional patients with obstetrical syndromes from the parent cohort. Pregnant women were classified into six groups: 1) term delivery without pregnancy complications (n=540; control); 2) preterm labor and delivery (n=203); 3) preterm premature rupture of the membranes (n=112); 4) preeclampsia (n=230); 5) small-for-gestational-age neonate (n=334); and 6) other pregnancy complications (n=182). Maternal plasma concentrations of PlGF and sFlt-1 were determined by enzyme-linked immunosorbent assays in 7560 longitudinal samples. Placental pathologists, masked to clinical outcomes, diagnosed the presence or absence of placental lesions of maternal vascular malperfusion. Comparisons between mean biomarker concentrations in cases and controls were performed by utilizing longitudinal generalized additive models. Comparisons were made between controls and each obstetrical syndrome with and without subclassifying cases according to the presence or absence of placental lesions of maternal vascular malperfusion.

RESULTS

1) When obstetrical syndromes are classified based on the presence or absence of placental lesions of maternal vascular malperfusion, significant differences in the mean plasma concentrations of PlGF, sFlt-1, and the PlGF/sFlt-1 ratio between cases and controls emerge earlier in gestation; 2) the strength of association between an abnormal PlGF/sFlt-1 ratio and the occurrence of obstetrical syndromes increases when placental lesions of maternal vascular malperfusion are present (adjusted odds ratio [aOR], 13.6 vs 6.7 for preeclampsia; aOR, 8.1 vs 4.4 for small-for-gestational-age neonates; aOR, 5.5 vs 2.1 for preterm premature rupture of the membranes; and aOR, 3.3 vs 2.1 for preterm labor (all P<0.05); and 3) the PlGF/sFlt-1 ratio at 28 to 32 weeks of gestation is abnormal in patients who subsequently delivered due to preterm labor with intact membranes and in those with preterm premature rupture of the membranes if both groups have placental lesions of maternal vascular malperfusion. Such association is not significant in patients with these obstetrical syndromes who do not have placental lesions.

CONCLUSION

Classification of obstetrical syndromes according to the presence or absence of placental lesions of maternal vascular malperfusion allows biomarkers to be informative earlier in gestation and enhances the strength of association between biomarkers and clinical outcomes. We propose that a new taxonomy of obstetrical disorders informed by placental pathology will facilitate the discovery and implementation of biomarkers as well as the prediction and prevention of such disorders.

The association between protein levels in 24-hour urine samples and maternal and neonatal outcomes of pregnant women with preeclampsia

Objective

Hypertensive diseases of pregnancy are one of the leading causes of maternal and perinatal mortality worldwide. The aim of this study was to evaluate the association between protein levels in 24-hour urine samples and maternal and perinatal outcomes in preeclamptic patients.

Material and Methods

This retrospective cohort study was conducted with pregnant women who were diagnosed with preeclampsia (PE) and delivered in our clinic between 2010 and 2018. Patients were divided into those with a proteinuria value below 300 mg/24 h (non-proteinuria), proteinuria value between 300-2000 mg/24 h (mild proteinuria), proteinuria value between 2000-5000 mg/24 h (severe proteinuria) and proteinuria value >5000 mg/24 h (massive proteinuria) and were compared in terms of maternal and perinatal outcomes. Demographic characteristics (age, body mass index in kg/m2, gravidity), PE-related clinical symptoms (epigastric pain, neurological and respiratory symptoms), laboratory findings (24 h protein level, lactate dehydrogenase, aspartate aminotransferase, platelet count and creatine levels) were recorded in all patients.

Results

A total of 1,379 patients meeting the study criteria were included. There were 315 (23%) patients in the non-proteinuria group, 704 (51%) in the mild proteinuria group, 234 (17%) patients in the severe group and 126 (9%) patients in the massive proteinuria group. The massive proteinuria group was found to have the highest rates of maternal and prenatal complications. The Apgar score, umbilical cord pH value, birth weight, gestational week at delivery, intrauterine growth restriction and intrauterine fetal death were significantly higher in the massive proteinuria group.

Conclusion

Our data showed that the degree of proteinuria appears to be associated with maternal, fetal and neonatal outcomes among women diagnosed with PE. Women with proteinuria of >5000 mg/24 hours had notably poorer natal outcomes.

Pregnancy-specific responses to COVID-19 are revealed by high-throughput proteomics of human plasma

Pregnant women are at greater risk of adverse outcomes, including mortality, as well as obstetrical complications resulting from COVID-19. However, pregnancy-specific changes that underlie such worsened outcomes remain unclear. Herein, we profiled the plasma proteome of pregnant and non-pregnant COVID-19 patients and controls and showed alterations that display a dose-response relationship with disease severity; yet, such proteomic perturbations are dampened during pregnancy. In both pregnant and non-pregnant state, the proteome response induced by COVID-19 showed enrichment of mediators implicated in cytokine storm, endothelial dysfunction, and angiogenesis. Shared and pregnancy-specific proteomic changes were identified: pregnant women display a tailored response that may protect the conceptus from heightened inflammation, while non-pregnant individuals display a stronger response to repel infection. Furthermore, the plasma proteome can accurately identify COVID-19 patients, even when asymptomatic or with mild symptoms. This study represents the most comprehensive characterization of the plasma proteome of pregnant and non-pregnant COVID-19 patients.

Evaluating the predictive value of fetal Doppler indices and neonatal outcome in late-onset preeclampsia with severe features: a cross-sectional study in a resource-limited setting

Background

Preeclampsia constitutes a major health problem with substantial maternal and perinatal morbidity and mortality. The aim of this study was to detect the diagnostic efficacy of fetal Doppler in predicting adverse outcomes in severe late onset preeclampsia (LOP).

Methods

A prospective study was conducted among childbearing women who presented with severe LOP and matched controls. Umbilical artery (UA) and middle cerebral artery (MCA) Doppler indices including pulsatility index (PI), resistance index (RI), systolic/diastolic ratio (S/D) and cerebroplacental ratio (CPR) were measured.

Results

All UA indices were significantly higher in the case group compared to the controls (p < 0.001). UA PI and RI were significantly correlated with all neonatal adverse outcomes except cord pH status (p < 0.05). Abnormal CPR was the most sensitive index that positively correlated with intrauterine growth retardation (IUGR), low 5- minute Apgar score and neonatal intensive care unit admission (79, 72.8 and 73.3%, respectively). In the same context, Abnormal UA PI and RI represented the most specific tool for predicting IUGR, low 1- and 5- minutes Apgar score with positive predictive values were 52, 87 and 57%, respectively.

Conclusion

In severe LOP, UA Doppler remains the preferential indicator for adverse birth outcomes with CPR is the best index that could be solely used for predicting such outcome.

Second-trimester serum high mobility group box-1 and uterine artery Doppler to predict preeclampsia

The objective of this study was to identify the predictive value for preeclampsia of second-trimester serum high mobility group box-1 (HMGB1) and uterine artery Doppler in singleton pregnancies. Between April 2020 and April 2021, a prospective study was conducted on singleton pregnancies with a gestational age of 16–20⁺⁶ weeks at King Chulalongkorn Memorial Hospital, Department of Obstetrics and Gynecology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. Maternal characteristics, uterine artery Doppler, and serum HMGB1 were collected. Serum HMGB1 levels and mean uterine artery pulsatility index (UAPI) were combined to calculate the predictive value for preeclampsia. A total of 393 pregnant women were analyzed, with 25 cases (6.4%) developing preeclampsia and 5 cases (1.3%) developing early-onset preeclampsia. Baseline characteristics of preeclampsia and normal pregnant women were comparable. Preeclamptic pregnant women had significantly higher mean serum HMGB1 levels than normal pregnant women (1112.8 ± 363.1 ng/mL vs 910.8 ± 486.1 ng/mL, p = 0.013). There was no difference in the mean UAPI. Any early-diastolic notching was found more frequently in the preeclampsia group (32.0% vs 12.5%, p = 0.013). The cut-off value for serum HMGB1 levels above 1.04 MoM as abnormal value to predict preeclampsia had sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 88.0%, 53.5%, 11.4% and 98.5%, respectively. When using abnormal serum HMGB1 levels combined with mean UAPI above 95th percentile, the sensitivity, specificity, PPV and NPV to predict preeclampsia were 88.0%, 50.8%, 10.8% and 98.4%, respectively. This study showed that serum HMGB1 at 16–20⁺⁶ weeks of gestation were effective in predicting preeclampsia. The addition of UAPI did not improve the prediction performance.

Preeclampsia: state of art and future perspectives. A special focus on possible preventions

Preeclampsia (PE) is characterised by the new onset of hypertension after the 20th week of pregnancy, with or without proteinuria or hypertension that leads to end-organ dysfunction. Since the only definitive treatment is delivery, PE still represents one of the leading causes of preterm birth and perinatal mobility and mortality. Therefore, any strategies that aim to reduce adverse outcomes are based on early primary prevention, prenatal surveillance and prophylactic interventions. In the last decade, intense research has been focussed on the study of predictive models in order to identify women at higher risk accurately. To date, the most effective screening model is based on the combination of anamnestic, demographic, biophysical and maternal biochemical factors. In this review, we provide a detailed discussion about the current and future perspectives in the field of PE. We will examine pathogenesis, risk factors and clinical features. Moreover, recent developments in screening and prevention strategies, novel therapies and healthcare management strategies will be discussed.

The amniotic fluid proteome changes with gestational age in normal pregnancy: a cross-sectional study

The cell-free transcriptome in amniotic fluid (AF) has been shown to be informative of physiologic and pathologic processes in pregnancy; however, the change in AF proteome with gestational age has mostly been studied by targeted approaches. The objective of this study was to describe the gestational age-dependent changes in the AF proteome during normal pregnancy by using an omics platform. The abundance of 1310 proteins was measured on a high-throughput aptamer-based proteomics platform in AF samples collected from women during midtrimester (16-24 weeks of gestation, n = 15) and at term without labor (37-42 weeks of gestation, n = 13). Only pregnancies without obstetrical complications were included in the study. Almost 25% (320) of AF proteins significantly changed in abundance between the midtrimester and term gestation. Of these, 154 (48.1%) proteins increased, and 166 (51.9%) decreased in abundance at term compared to midtrimester. Tissue-specific signatures of the trachea, salivary glands, brain regions, and immune system were increased while those of the gestational tissues (uterus, placenta, and ovary), cardiac myocytes, and fetal liver were decreased at term compared to midtrimester. The changes in AF protein abundance were correlated with those previously reported in the cell-free AF transcriptome. Intersecting gestational age-modulated AF proteins and their corresponding mRNAs previously reported in the maternal blood identified neutrophil-related protein/mRNA pairs that were modulated in the same direction. The first study to utilize an aptamer-based assay to profile the AF proteome modulation with gestational age, it reveals that almost one-quarter of the proteins are modulated as gestation advances, which is more than twice the fraction of altered plasma proteins (~ 10%). The results reported herein have implications for future studies focused on discovering biomarkers to predict, monitor, and diagnose obstetrical diseases.

Maternal circulating concentrations of soluble Fas and Elabela in early- and late-onset preeclampsia

OBJECTIVE

The Fas/Fas ligand (FASL) system and Elabela-apelin receptor signaling pathways are implicated in the pathophysiology of preeclampsia. The aim of the current study was to investigate whether a model combining the measurement of sFas and Elabela in the maternal circulation may serve as a clinical biomarker for early- and/or late-onset preeclampsia more effectively than measures of each biomarker individually.

METHODS

Blood samples were collected from 214 women in the following groups: (1) normal pregnancy sampled <34 weeks of gestation (n = 56); (2) patients who developed early-onset preeclampsia (n = 54); (3) normal pregnancy sampled ≥34 weeks of gestation (n = 52); (4) patients who developed late-onset preeclampsia (n = 52). Maternal circulating soluble Fas and Elabela concentrations were determined using sensitive and validated immunoassays. Two sample t-tests, multivariate logistic regression, and receiver operating characteristic curves were used for analyses.

RESULTS

(1) Women with early-onset preeclampsia, and those with late-onset preeclampsia with placental lesions of maternal vascular malperfusion, had increased concentrations of sFas compared to their gestational age-matched normal controls; (2) women with late-onset preeclampsia, but not those with early-onset preeclampsia, had increased concentrations of Elabela compared to their gestational age-matched counterparts; and (3) an increase in both Elabela and sFas concentrations was more strongly associated with late-onset preeclampsia than early-onset preeclampsia relative to models including either of the markers alone.

CONCLUSIONS

A combined model of maternal sFas and Elabela concentrations provides a stronger association with late-onset preeclampsia than either protein alone. This finding demonstrates the possibility to improve the classification of late-onset preeclampsia by combining the results of both molecular biomarkers.

Prediction of preeclampsia throughout gestation with maternal characteristics and biophysical and biochemical markers: a longitudinal study

BACKGROUND

The current approach to predict preeclampsia combines maternal risk factors and evidence from biophysical markers (mean arterial pressure, Doppler velocimetry of the uterine arteries) and maternal blood proteins (placental growth factor, soluble vascular endothelial growth factor receptor-1, pregnancy-associated plasma protein A). Such models require the transformation of biomarker data into multiples of the mean values by using population- and site-specific models. Previous studies have focused on a narrow window in gestation and have not included the maternal blood concentration of soluble endoglin, an important antiangiogenic factor up-regulated in preeclampsia.

OBJECTIVE

This study aimed (1) to develop models for the calculation of multiples of the mean values for mean arterial pressure and biochemical markers; (2) to build and assess the predictive models for preeclampsia based on maternal risk factors, the biophysical (mean arterial pressure) and biochemical (placental growth factor, soluble vascular endothelial growth factor receptor-1, and soluble endoglin) markers collected throughout pregnancy; and (3) to evaluate how prediction accuracy is affected by the presence of chronic hypertension and gestational age.

STUDY DESIGN

This longitudinal case-cohort study included 1150 pregnant women: women without preeclampsia with (n=49) and without chronic hypertension (n=871) and those who developed preeclampsia (n=166) or superimposed preeclampsia (n=64). Mean arterial pressure and immunoassay-based maternal plasma placental growth factor, soluble vascular endothelial growth factor receptor-1, and soluble endoglin concentrations were available throughout pregnancy (median of 5 observations per patient). A prior-risk model for preeclampsia was established by using Poisson regression based on maternal characteristics and obstetrical history. Next, multiple regression was used to fit biophysical and biochemical marker data as a function of maternal characteristics by using data collected at 8 to 15⁺⁶, 16 to 19⁺⁶, 20 to 23⁺⁶, 24 to 27⁺⁶, 28 to 31⁺⁶, and 32 to 36⁺⁶ week intervals, and observed values were converted into multiples of the mean values. Then, multivariable prediction models for preeclampsia were fit based on the biomarker multiples of the mean data and prior-risk estimates. Separate models were derived for overall, preterm, and term preeclampsia, which were evaluated by receiver operating characteristic curves and sensitivity at fixed false-positive rates.

RESULTS

(1) The inclusion of soluble endoglin in prediction models for all preeclampsia, together with the prior-risk estimates, mean arterial pressure, placental growth factor, and soluble vascular endothelial growth factor receptor-1, increased the sensitivity (at a fixed false-positive rate of 10%) for early prediction of superimposed preeclampsia, with the largest increase (from 44% to 54%) noted at 20 to 23⁺⁶ weeks (McNemar test, P<.05); (2) combined evidence from prior-risk estimates and biomarkers predicted preterm preeclampsia with a sensitivity (false-positive rate, 10%) of 55%, 48%, 62%, 72%, and 84% at 8 to 15⁺⁶, 16 to 19⁺⁶, 20 to 23⁺⁶, 24 to 27⁺⁶, and 28 to 31⁺⁶ week intervals, respectively; (3) the sensitivity for term preeclampsia (false-positive rate, 10%) was 36%, 36%, 41%, 43%, 39%, and 51% at 8 to 15⁺⁶, 16 to 19⁺⁶, 20 to 23⁺⁶, 24 to 27⁺⁶, 28 to 31⁺⁶, and 32 to 36⁺⁶ week intervals, respectively; (4) the detection rate for superimposed preeclampsia among women with chronic hypertension was similar to that in women without chronic hypertension, especially earlier in pregnancy, reaching at most 54% at 20 to 23⁺⁶ weeks (false-positive rate, 10%); and (5) prediction models performed comparably to the Fetal Medicine Foundation calculators when the same maternal risk factors and biomarkers (mean arterial pressure, placental growth factor, and soluble vascular endothelial growth factor receptor-1 multiples of the mean values) were used as input.

CONCLUSION

We introduced prediction models for preeclampsia throughout pregnancy. These models can be useful to identify women at risk during the first trimester who could benefit from aspirin treatment or later in pregnancy to inform patient management. Relative to prediction performance at 8 to 15⁺⁶ weeks, there was a substantial improvement in the detection rate for preterm and term preeclampsia by using data collected after 20 and 32 weeks' gestation, respectively. The inclusion of plasma soluble endoglin improves the early prediction of superimposed preeclampsia, which may be valuable when Doppler velocimetry of the uterine arteries is not available.

Maternal whole blood mRNA signatures identify women at risk of early preeclampsia: a longitudinal study

PURPOSE

To determine whether previously established mRNA signatures are predictive of early preeclampsia when evaluated by maternal cellular transcriptome analysis in samples collected before clinical manifestation.

MATERIALS AND METHODS

We profiled gene expression at exon-level resolution in whole blood samples collected longitudinally from 49 women with normal pregnancy (controls) and 13 with early preeclampsia (delivery <34 weeks of gestation). After preprocessing and removal of gestational age-related trends in gene expression, data were converted into Z-scores based on the mean and standard deviation among controls for six gestational-age intervals. The average Z-scores of mRNAs in each previously established signature considered herein were compared between cases and controls at 9-11, 11-17, 17-22, 22-28, 28-32, and 32-34 weeks of gestation.Results: (1) Average expression of the 16-gene untargeted cellular mRNA signature was higher in women diagnosed with early preeclampsia at 32-34 weeks of gestation, yet more importantly, also prior to diagnosis at 28-32 weeks and 22-28 weeks of gestation, compared to controls (all, p < .05). (2) A combination of four genes from this signature, including a long non-protein coding RNA [H19 imprinted maternally expressed transcript (H19)], fibronectin 1 (FN1), tubulin beta-6 class V (TUBB6), and formyl peptide receptor 3 (FPR3) had a sensitivity of 0.85 (0.55-0.98) and a specificity of 0.92 (0.8-0.98) for prediction of early preeclampsia at 22-28 weeks of gestation. (3) H19, FN1, and TUBB6 were increased in women with early preeclampsia as early as 11-17 weeks of gestation (all, p < .05). (4) After diagnosis at 32-34 weeks, but also prior to diagnosis at 11-17 weeks, women destined to have early preeclampsia showed a coordinated increase in whole blood expression of several single-cell placental signatures, including the 20-gene signature of extravillous trophoblast (all, p < .05). (5) A combination of three mRNAs from the extravillous trophoblast signature (MMP11, SLC6A2, and IL18BP) predicted early preeclampsia at 11-17 weeks of gestation with a sensitivity of 0.83 (0.52-0.98) and specificity of 0.94 (0.79-0.99).

CONCLUSIONS

Circulating early transcriptomic markers for preeclampsia can be found either by untargeted profiling of the cellular transcriptome or by focusing on placental cell-specific mRNAs. The untargeted cellular mRNA signature was consistently increased in early preeclampsia after 22 weeks of gestation, and individual mRNAs of this signature were significantly increased as early as 11-17 weeks of gestation. Several single-cell placental signatures predicted future development of the disease at 11-17 weeks and were also increased in women already diagnosed at 32-34 weeks of gestation.

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.

Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth

Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics study coupled with a DREAM challenge to develop predictive models of PTB. The findings indicate that whole-blood gene expression predicts ultrasound-based gestational ages in normal and complicated pregnancies (r = 0.83) and, using data collected before 37 weeks of gestation, also predicts the delivery date in both normal pregnancies (r = 0.86) and those with spontaneous preterm birth (r = 0.75). Based on samples collected before 33 weeks in asymptomatic women, our analysis suggests that expression changes preceding preterm prelabor rupture of the membranes are consistent across time points and cohorts and involve leukocyte-mediated immunity. Models built from plasma proteomic data predict spontaneous preterm delivery with intact membranes with higher accuracy and earlier in pregnancy than transcriptomic models (AUROC = 0.76 versus AUROC = 0.6 at 27-33 weeks of gestation).

Unravelling the potential of angiogenic factors for the early prediction of preeclampsia

Preeclampsia is a multisystem, multiorgan hypertensive disorder of pregnancy responsible for maternal and perinatal morbidity and mortality in low- and middle-income countries. The classic diagnostic features hold less specificity for preeclampsia and its associated adverse outcomes, suggesting a need for specific and reliable biomarkers for the early prediction of preeclampsia. The imbalance of pro- and antiangiogenic circulatory factors contributes to the pathophysiology of preeclampsia. Several studies have examined the profile of angiogenic factors in preeclampsia to search for a biomarker that will improve the diagnostic ability of preeclampsia and associated adverse outcomes. This may help in more efficient patient management and the reduction of associated health care costs. This article reviews the findings from previous studies published to date on angiogenic factors and suggests a need to apply a multivariable model from the beginning of pregnancy and continuing throughout gestation for the early and specific prediction of preeclampsia.

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.

Quantitative proteomics-based analyses performed on pre-eclampsia samples in the 2004-2020 period: a systematic review

BACKGROUND

Quantitative proteomics is an invaluable tool in biomedicine for the massive comparative analysis of protein component of complex biological samples. In the last two decades, this technique has been used to describe proteins potentially involved in the pathophysiological mechanisms of preeclampsia as well as to identify protein biomarkers that could be used with diagnostic/prognostic purposes in pre-eclampsia.

RESULTS

We have done a systematic review of all proteomics-based papers describing differentially expressed proteins in this disease. Searching Pubmed with the terms pre-eclampsia and proteomics, restricted to the Title/Abstract and to MeSH fields, and following manual curation of the original list, retrieved 69 original articles corresponding to the 2004-2020 period. We have only considered those results based on quantitative, unbiased proteomics studies conducted in a controlled manner on a cohort of control and pre-eclamptic individuals. The sources of biological material used were serum/plasma (n = 32), placenta (n = 23), urine (n = 9), cerebrospinal fluid (n = 2), amniotic fluid (n = 2) and decidual tissue (n = 1). Overall results were filtered based on two complementary criteria. First, we have only accounted all those proteins described in at least two (urine), three (placenta) and four (serum/plasma) independent studies. Secondly, we considered the consistency of the quantitative data, that is, inter-study agreement in the protein abundance control/pre-eclamptic ratio. The total number of differential proteins in serum/plasma (n = 559), placenta (n = 912), urine (n = 132) and other sources of biological material (n = 26), reached 1631 proteins. Data were highly complementary among studies, resulting from differences on biological sources, sampling strategies, patient stratification, quantitative proteomic analysis methods and statistical data analysis. Therefore, stringent filtering was applied to end up with a cluster of 18, 29 and 16 proteins consistently regulated in pre-eclampsia in placenta, serum/plasma and urine, respectively. The systematic collection, standardization and evaluation of the results, using diverse filtering criteria, provided a panel of 63 proteins whose levels are consistently modified in the context of pre-eclampsia.

Unveiling molecular signatures of preeclampsia and gestational diabetes mellitus with multi-omics and innovative cheminformatics visualization tools

To fully enable the development of diagnostic tools and progressive pharmaceutical drugs, it is imperative to understand the molecular changes occurring before and during disease onset and progression. Systems biology assessments utilizing multi-omic analyses (e.g. the combination of proteomics, lipidomics, genomics, etc.) have shown enormous value in determining molecules prevalent in diseases and their associated mechanisms. Herein, we utilized multi-omic evaluations, multi-dimensional analysis methods, and new cheminformatics-based visualization tools to provide an in depth understanding of the molecular changes taking place in preeclampsia (PRE) and gestational diabetes mellitus (GDM) patients. Since PRE and GDM are two prevalent pregnancy complications that result in adverse health effects for both the mother and fetus during pregnancy and later in life, a better understanding of each is essential. The multi-omic evaluations performed here provide new insight into the end-stage molecular profiles of each disease, thereby supplying information potentially crucial for earlier diagnosis and treatments.

Clinical Procedures for the Prevention of Preeclampsia in Pregnant Women: A Systematic Review

OBJECTIVE

 To identify the most effective procedures recommended for the prevention of preeclampsia.

DATA SOURCES

 A systematic review was performed in the following databases: Pubmed/MEDLINE, CINAHL, Web of Science, Cochrane and LILACS via the Virtual Health Library (VHL). A manual search was also performed to find additional references. The risk of bias, the quality of the evidence, and the classification of the strength of the recommendations were evaluated using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

SELECTION OF STUDIES

 In the initial search in the databases, the total number of articles retrieved was 351, and 2 were retrieved through the manual search; after duplicate articles were removed, 333 citations remained. After a thorough review of the titles and abstracts, 315 references were excluded. Accordingly, 18 articles were maintained for selection of the complete text (phase 2). This process led to the exclusion of 6 studies. In total, 12 articles were selected for data extraction and qualitative synthesis.

DATA COLLECTION

 The articles selected for the study were analyzed, and we inserted the synthesis of the evidence in the online software GRADEpro Guideline Development Tool (GDT) (McMaster University and Evidence Prime Inc. All right reserved. McMaster University, Hamilton, Ontário, Canada); thus, it was possible to develop a table of evidence, with the quality of the evidence and the classification of the strength of the recommendations.

DATA SYNTHESIS

 In total, seven studies recommended the individual use of aspirin, or aspirin combined with calcium, heparin or dipyridamole. The use of calcium alone or in combination with phytonutrients was also highlighted. All of the studies were with women at a high risk of developing preeclampsia.

CONCLUSION

 According to the studies evaluated, the administration of aspirin is still the best procedure to be used in the clinical practice to prevent preeclampsia.