A review of omics approaches to study preeclampsia

Construction of a pathway-level model for preeclampsia based on gene expression data

Preeclampsia (PE) is a heterogeneous disease that seriously affects the health of mothers and fetuses. Lack of detection assays, its diagnosis and intervention are often delayed when the clinical symptoms are atypical. Using personalized pathway-based analysis and machine learning algorithms, we built a PE diagnosis model consisting of nine core pathways using multiple cohorts from the Gene Expression Omnibus database. The model showed an area under the receiver operating characteristic (AUROC) curve of 0.959 with the data from the placental tissue samples in the development cohort. In the two validation cohorts, the AUROCs were 0.898 and 0.876, respectively. The model also performed well with the maternal plasma data in another validation cohort (AUROC: 0.815). Moreover, we identified tyrosine-protein kinase Lck (LCK) as the hub gene in this model and found that LCK and pLCK proteins were downregulated in placentas from PE patients. The pathway-level model for PE can provide a novel direction to develop molecular diagnostic assay and investigate potential mechanisms of PE in future studies.

Metabolomic prediction of severe maternal and newborn complications in preeclampsia

INTRODUCTION

Preeclampsia (PreE) remains a major source of maternal and newborn complications. Prenatal prediction of these complications could significantly improve pregnancy management.

OBJECTIVES

Using metabolomic analysis we investigated the prenatal prediction of maternal and newborn complications in early and late PreE and investigated the pathogenesis of such complications.

METHODS

Serum samples from 76 cases of PreE (36 early-onset and 40 late-onset), and 40 unaffected controls were collected. Direct Injection Liquid Chromatography-Mass Spectrometry combined with Nuclear Magnetic Resonance (NMR) spectroscopy was performed. Logistic regression analysis was used to generate models for prediction of adverse maternal and neonatal outcomes in patients with PreE. Metabolite set enrichment analysis (MSEA) was used to identify the most dysregulated metabolites and pathways in PreE.

RESULTS

Forty-three metabolites were significantly altered (p < 0.05) in PreE cases with maternal complications and 162 metabolites were altered in PreE cases with newborn adverse outcomes. The top metabolite prediction model achieved an area under the receiver operating characteristic curve (AUC) = 0.806 (0.660-0.952) for predicting adverse maternal outcomes in early-onset PreE, while the AUC for late-onset PreE was 0.843 (0.712-0.974). For the prediction of adverse newborn outcomes, regression models achieved an AUC = 0.828 (0.674-0.982) in early-onset PreE and 0.911 (0.828-0.994) in late-onset PreE. Profound alterations of lipid metabolism were associated with adverse outcomes.

CONCLUSION

Prenatal metabolomic markers achieved robust prediction, superior to conventional markers for the prediction of adverse maternal and newborn outcomes in patients with PreE. We report for the first-time the prediction and metabolomic basis of adverse maternal and newborn outcomes in patients with PreE.

Discover overlooked complications after preeclampsia using electronic health records

Background

Preeclampsia (PE) is a severe pregnancy complication characterized by hypertension and end-organ damage such as proteinuria. PE poses a significant threat to women's long-term health, including an increased risk of cardiovascular and renal diseases. Most previous studies have been hypothesis-based, potentially overlooking certain significant complications. This study conducts a comprehensive, non-hypothesis-based analysis of PE-complicated diagnoses after pregnancies using multiple large-scale electronic health records (EHR) datasets.

Method

From the University of Michigan (UM) Healthcare System, we collected 4,348 PE patients for the cases and 27,377 patients with pregnancies not complicated by PE or related conditions for the controls. We first conducted a non-hypothesis-based analysis to identify any long-term adverse health conditions associated with PE using logistic regression with adjustments to demographics, social history, and medical history. We confirmed the identified complications with UK Biobank data which contain 443 PE cases and 14,870 non-PE controls. We then conducted a survival analysis on complications that exhibited significance in more than 5 consecutive years post-PE. We further examined the potential racial disparities of identified complications between Caucasian and African American patients.

Findings

Uncomplicated hypertension, complicated diabetes, congestive heart failure, renal failure, and obesity exhibited significantly increased risks whereas hypothyroidism showed decreased risks, in 5 consecutive years after PE in the UM discovery data. UK Biobank data confirmed the increased risks of uncomplicated hypertension, complicated diabetes, congestive heart failure, renal failure, and obesity. Further survival analysis using UM data indicated significantly increased risks in uncomplicated hypertension, complicated diabetes, congestive heart failure, renal failure, and obesity, and significantly decreased risks in hypothyroidism. There exist racial differences in the risks of developing hypertension and hypothyroidism after PE. PE protects against hypothyroidism in African American postpartum women but not Cacausians; it also increases the risks of uncomplicated hypertension but less severely in African American postpartum women as compared to Cacausians.

Interpretation

This study addresses the lack of a comprehensive examination of PE's long-term effects utilizing large-scale EHR and advanced statistical methods. Our findings underscore the need for long-term monitoring and interventions for women with a history of PE, emphasizing the importance of personalized postpartum care. Notably, the racial disparities observed in the impact of PE on hypertension and hypothyroidism highlight the necessity of tailored aftercare based on race.

Discover overlooked complications after preeclampsia using electronic health records

Background

Preeclampsia (PE) is a severe pregnancy complication characterized by hypertension and end-organ damage such as proteinuria. PE poses a significant threat to women's long-term health, including an increased risk of cardiovascular and renal diseases. Most previous studies have been hypothesis-based, potentially overlooking certain significant complications. This study conducts a comprehensive, non-hypothesis-based analysis of PE-complicated diagnoses after pregnancies using multiple large-scale electronic health records (EHR) datasets.

Method

From the University of Michigan (UM) Healthcare System, we collected 4,348 PE patients for the cases and 27,377 patients with pregnancies not complicated by PE or related conditions for the controls. We first conducted a non-hypothesis-based analysis to identify any long-term adverse health conditions associated with PE using logistic regression with adjustments to demographics, social history, and medical history. We confirmed the identified complications with UK Biobank data which contain 443 PE cases and 14,870 non-PE controls. We then conducted a survival analysis on complications that exhibited significance in more than 5 consecutive years post-PE. We further examined the potential racial disparities of identified complications between Caucasian and African American patients.

Findings

Uncomplicated hypertension, complicated diabetes, congestive heart failure, renal failure, and obesity exhibited significantly increased risks whereas hypothyroidism showed decreased risks, in 5 consecutive years after PE in the UM discovery data. UK Biobank data confirmed the increased risks of uncomplicated hypertension, complicated diabetes, congestive heart failure, renal failure, and obesity. Further survival analysis using UM data indicated significantly increased risks in uncomplicated hypertension, complicated diabetes, congestive heart failure, renal failure, and obesity, and significantly decreased risks in hypothyroidism. There exist racial differences in the risks of developing hypertension and hypothyroidism after PE. PE protects against hypothyroidism in African American postpartum women but not Cacausians; it also increases the risks of uncomplicated hypertension but less severely in African American postpartum women as compared to Cacausians.

Interpretation

This study addresses the lack of a comprehensive examination of PE's long-term effects utilizing large-scale EHR and advanced statistical methods. Our findings underscore the need for long-term monitoring and interventions for women with a history of PE, emphasizing the importance of personalized postpartum care. Notably, the racial disparities observed in the impact of PE on hypertension and hypothyroidism highlight the necessity of tailored aftercare based on race.

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.

A cross-sectional analysis of syncytiotrophoblast membrane extracellular vesicles-derived transcriptomic biomarkers in early-onset preeclampsia

Background

Preeclampsia (PE) is a pregnancy-specific hypertensive disorder affecting 2%-8% of pregnancies worldwide. Biomarker(s) for the disorder exists, but while these have excellent negative predictive value, their positive predictive value is poor. Extracellular vesicles released by the placenta into the maternal circulation, syncytiotrophoblast membrane extracellular vesicles (STB-EVs), have been identified as being involved in PE with the potential to act as liquid biopsies.

Objective

The objective of this study was to identify the difference in the transcriptome of placenta and STB-EVs between preeclampsia and normal pregnancy (NP) and mechanistic pathways.

Methods/study design

We performed RNA-sequencing on placental tissue, medium/large and small STB-EVs from PE (n = 6) and NP (n = 6), followed by bioinformatic analysis to identify targets that could be used in the future for EV-based diagnostic tests for preeclampsia. Some of the identified biomarkers were validated with real-time polymerase chain reactions.

Results

Our analysis identified a difference in the transcriptomic STB-EV cargo between PE and NP. We then identified and verified the differential expression of FLNB, COL17A1, SLC45A4, LEP, HTRA4, PAPP-A2, EBI3, HSD17B1, FSTL3, INHBA, SIGLEC6, and CGB3. Our analysis also identified interesting mechanistic processes via an in silico prediction of STB-EV-based mechanistic pathways.

Conclusions

In this study, using comprehensive profiling of differentially expressed/carried genes of three linked sample subtypes in PE, we identified potential biomarkers and mechanistic gene pathways that may be important in the pathophysiology of PE and could be further explored in future studies.

Missing links in preeclampsia cell model systems of endothelial dysfunction

Preeclampsia, one of the main hypertensive disorders of pregnancy, is associated with circulating factors released by the ischemic placenta accompanied by systemic endothelial dysfunction. The etiology of preeclampsia remains poorly understood although it is associated with high maternal and fetal mortality and increased cardiovascular disease risk. Most cell model systems used for studying endothelial dysfunction have not taken into account hemodynamic physical factors such as shear-stress forces which may prevent extrapolation of cell data to in vivo settings. We overview the role of hemodynamic forces in modulating endothelial cell function and discuss strategies to reproduce this biological characteristic in vitro to improve our understanding of endothelial dysfunction associated with preeclampsia.

Placental transcriptome analysis of hypertensive pregnancies identifies distinct gene expression profiles of preeclampsia superimposed on chronic hypertension

BACKGROUND

The pathogenesis of preeclampsia superimposed on chronic hypertension (SI) is poorly understood relative to preeclampsia (PreE) occurring in pregnant people without chronic hypertension. Placental transcriptomes in pregnancies complicated by PreE and SI have not been previously compared.

METHODS

We identified pregnant people in the University of Michigan Biorepository for Understanding Maternal and Pediatric Health with hypertensive disorders affecting singleton, euploid gestations (N = 36) along with non-hypertensive control subjects (N = 12). Subjects were grouped as: (1) normotensive (N = 12), (2) chronic hypertensive (N = 13), (3) preterm PreE with severe features (N = 5), (4) term PreE with severe features (N = 11), (5) preterm SI (N = 3), or (6) term SI (N = 4). Bulk RNA sequencing of paraffin-embedded placental tissue was performed. The primary analysis assessed differential gene expression relative to normotensive and chronic hypertensive placentas, where Wald adjusted P values < 0.05 were considered significant. Unsupervised clustering analyses and correlation analyses were performed between conditions of interest, and a gene ontology was constructed.

RESULTS

Comparing samples from pregnant people with hypertensive diseases to non-hypertensive controls, there were 2290 differentially expressed genes. The log2-fold changes in genes differentially expressed in chronic hypertension correlated better with term (R = 0.59) and preterm (R = 0.63) PreE with severe features than with term (R = 0.21) and preterm (R = 0.22) SI. A relatively poor correlation was observed between preterm SI and preterm PreE with severe features (0.20) as well as term SI and term PreE with severe features (0.31). The majority of significant genes were downregulated in term and preterm SI versus normotensive controls (92.1%, N = 128). Conversely, most term and preterm PreE with severe features genes were upregulated compared to the normotensive group (91.8%, N = 97). Many of the upregulated genes in PreE with the lowest adjusted P values are known markers of abnormal placentation (e.g., PAAPA, KISS1, CLIC3), while the downregulated genes with the greatest adjusted P values in SI have fewer known pregnancy-specific functions.

CONCLUSIONS

We identified unique placental transcriptional profiles in clinically relevant subgroups of individuals with hypertension in pregnancy. Preeclampsia superimposed on chronic hypertension was molecularly distinct from preeclampsia in individuals without chronic hypertension, and chronic hypertension without preeclampsia, suggesting that preeclampsia superimposed on hypertension may represent a distinct entity.

The forkhead box protein P3 gene rs3761548 promoter polymorphism confers a genetic contribution to the risk of preeclampsia: A systematic review and meta-analysis

Various studies have investigated the risk of preeclampsia with the forkhead box protein P3 (FOXP3) gene rs2232365 and rs3761548 polymorphisms. However, the results remained contradictory. A comprehensive literature search was conducted using the Cochrane Library, PubMed, and Web of Science (up to Oct 11, 2021). Meta-analysis was carried out in the R language environment for statistical computing and graphics. A fixed-effect or random-effects model was used according to the statistical significance of heterogeneity among included studies. The pooled odds ratios and corresponding 95% confidence intervals were calculated to estimate the strength of the effect. For the rs2232365 polymorphism, statistical significance was detected neither in the overall population nor among the East Asian and West Asian subgroups. However, for rs3761548, the summarized statistics revealed a significant association between the C allele carriage and preeclampsia risk in the homozygote, heterozygote, and dominant models. The further stratified analysis found this effect might be specific to West-South Asian ethnic subgroups. To sum up, this meta-analysis showed that the FOXP3 rs3761548 polymorphism was significantly associated with preeclampsia susceptibility, and it had a deleterious effect especially in the West-South Asian population. In contrast, rs2232365 may serve as neither a protective nor a risk factor for preeclampsia onset.

Integrated Proteomic and N-Glycoproteomic Profiling of Placental Tissues of Patients with Preeclampsia

Background

Preeclampsia (PE) is a multi-system disorder of pregnancy that poses a serious threat to maternal and perinatal health worldwide. This study aims to evaluate the global alterations of protein expression and N-glycosylations that are crucial for PE pathogenesis. Here, tandem mass tag labeling combined with LC-MS/MS was employed to determine the global expression of all proteins and intact glycopeptide in placentas from three healthy pregnant women, three patients with early-onset severe PE, and three patients with late-onset severe PE.

Results

A total of 2260 proteins were quantified across 9 placental tissues, of which 37 and 23 were differentially expressed in the early-onset and late-onset PE groups, compared to the controls. A total of 789 glycopeptides were accurately quantified, which were derived from 204 glycosylated sites in 159 glycoproteins and were modified by 59 N-Linked glycans. A total of 123 differently expressed glycopeptides, which were from 47 glycoproteins were identified among three groups. Through a combined analysis of proteomic and glycoproteomic data, it was found that the changes in 10 glycoproteins were caused by the difference in glycosylation level but not in the protein abundance level.

Conclusion

This is the first study to conduct an integrated proteomic and glycoproteomic characterization of placental tissues of PE patients. Our findings suggest that glycosylation modification may affect the molecular function of proteins through changes in the glycosylation structure or the occupancy of glycosylation, which will provide new insights to help elucidating the pathogenic mechanism of PE.

Placental telomere length shortening is not associated with severe preeclampsia but the gestational age

Variations in telomere length (TL) have been associated with aging, stress, and many diseases. Placenta TL is an essential molecular component influencing the outcome of birth. Previous investigations into the relationship between placenta TL and preeclampsia (PE) have produced conflicting findings. We conducted a retrospective case-control analysis in this study to address the disparity. We used placenta samples from 224 births received from Hawaii Biorepository (HiBR) between 2006 and 2013, comprising 129 healthy full-term controls and 95 severe PE samples. The average absolute placental TL was calculated using the quantitative polymerase chain reaction (qPCR) technique. We utilized multiple linear regressions to associate placental TL with severe PE and other demographic, clinical and physiological data. The outcome demonstrates that the placental TL of severe PE cases did not significantly differ from that of healthy controls. Instead, there is a strong correlation between gestational age and placenta TL shortening. Placental TL also exhibits racial differences: (1) Latino moms' TL is significantly longer than non-Latino mothers' (p=0.009). (2) Caucasian patients with severe PE have shorter TL than non-Caucasian patients (p=0.0037). This work puts the long-standing question of whether severe PE influences placental TL to rest. Placental TL is not related to severe PE but is negatively associated with gestational age and is also affected by race.

Early prediction and longitudinal modeling of preeclampsia from multiomics

Preeclampsia is a complex disease of pregnancy whose physiopathology remains unclear. We developed machine-learning models for early prediction of preeclampsia (first 16 weeks of pregnancy) and over gestation by analyzing six omics datasets from a longitudinal cohort of pregnant women. For early pregnancy, a prediction model using nine urine metabolites had the highest accuracy and was validated on an independent cohort (area under the receiver-operating characteristic curve [AUC] = 0.88, 95% confidence interval [CI] [0.76, 0.99] cross-validated; AUC = 0.83, 95% CI [0.62,1] validated). Univariate analysis demonstrated statistical significance of identified metabolites. An integrated multiomics model further improved accuracy (AUC = 0.94). Several biological pathways were identified including tryptophan, caffeine, and arachidonic acid metabolisms. Integration with immune cytometry data suggested novel associations between immune and proteomic dynamics. While further validation in a larger population is necessary, these encouraging results can serve as a basis for a simple, early diagnostic test for preeclampsia.

Identification of Key Genes and Pathways Associated with Preeclampsia by a WGCNA and an Evolutionary Approach

Preeclampsia (PE) is the serious obstetric-related disease characterized by newly onset hypertension and causes damage to the kidneys, brain, liver, and more. To investigate genes with key roles in PE’s pathogenesis and their contributions, we used a microarray dataset of normotensive and PE patients and conducted a weighted gene co-expression network analysis (WGCNA). Cyan and magenta modules that are highly enriched with differentially expressed genes (DEGs) were revealed. By using the molecular complex detection (MCODE) algorithm, we identified five significant clusters in the cyan module protein–protein interaction (PPI) network and nine significant clusters in the magenta module PPI network. Our analyses indicated that (i) human accelerated region (HAR) genes are enriched in the magenta-associated C6 cluster, and (ii) positive selection (PS) genes are enriched in the cyan-associated C3 and C5 clusters. We propose these enriched HAR and PS genes, i.e., EIF4E, EIF5, EIF3M, DDX17, SRSF11, PSPC1, SUMO1, CAPZA1, PSMD14, and MNAT1, including highly connected hub genes, HNRNPA1, RBMX, PRKDC, and RANBP2, as candidate key genes for PE’s pathogenesis. A further clarification of the functions of these PPI clusters and key enriched genes will contribute to the discovery of diagnostic biomarkers for PE and therapeutic intervention targets.

Polygenic Risk Score and Risk Factors for Preeclampsia and Gestational Hypertension

Preeclampsia and gestational hypertensive disorders (GHD) are common complications of pregnancy that adversely affect maternal and offspring health, often with long-term consequences. High BMI, advanced age, and pre-existing conditions are known risk factors for GHD. Yet, assessing a woman's risk of GHD based on only these characteristics needs to be reevaluated in order to identify at-risk women, facilitate early diagnosis, and implement lifestyle recommendations. This study demonstrates that a risk score developed with machine learning from the case-control genetics dataset can be used as an early screening test for GHD. We further confirm BMI as a risk factor for GHD and investigate a relationship between GHD and genetically constructed anthropometric measures and biomarkers. Our results show that polygenic risk score can be used as an early screening tool that, together with other known risk factors and medical history, would assist in identifying women at higher risk of GHD before its onset to enable stratification of patients into low-risk and high-risk groups for monitoring and preventative programs to mitigate the risks.

Combined Effects of Methyldopa and Baicalein or Scutellaria baicalensis Roots Extract on Blood Pressure, Heart Rate, and Expression of Inflammatory and Vascular Disease-Related Factors in Spontaneously Hypertensive Pregnant Rats

The aim of the study was to investigate the effect of baicalein or Scutellaria baicalensis root extract interaction with methyldopa in pregnant spontaneously hypertensive rats (SHR) at the pharmacodynamic, molecular, and biochemical levels. The rats, after confirming pregnancy, received baicalein (200 mg/kg/day, p.o.) and extract (1000 mg/kg/day, p.o.), in combination with methyldopa (400 mg/kg/day; p.o.), for 14 consecutive days, 1 h before blood pressure and heart rate measurements. In the heart and placenta from mothers after giving birth to their offspring, mRNA expression of factors related to inflammatory processes (TNF-α, Il-1β, IL-6) and vascular diseases (TGF-β, HIF-1α, VEGF, PlGF) was measured. Levels of markers of oxidative stress (superoxide dismutase and malondialdehyde) in the placenta and indicators of myocardial damage (troponin cTnC and cTnI, creatine kinase, myoglobin, and lactate dehydrogenase) in the heart were also assessed. Baicalein co-administered with methyldopa was associated with reduced blood pressure, especially during the first three days. The interactions were more pronounced for such factors as TGF-β, HIF-1α, VEGF, and PlGF than TNF-α, Il-1β, and IL-6. Combined application of baicalein and extract with methyldopa may be of value in the development of a new antihypertensive medication intended for patients suffering from preeclampsia or pregnancy-induced hypertension.

A comprehensive analysis of metabolomics and transcriptomics to reveal major metabolic pathways and potential biomarkers of human preeclampsia placenta

Background: The etiology of preeclampsia (PE) remains unclear. With the utilization of metabolomics, dysregulated production of several metabolic components in human plasma, such as lipids, amino acids, androgens and estrogens, was found to be important in the pathogenesis of PE. Transcriptomics adds more in-depth information, and the integration of transcriptomics and metabolomics may yield further insight into PE pathogenesis than either one alone.

Objectives: We investigated the placental metabolomics and transcriptomics of PE patients to identify affected metabolic pathways and potential biological targets for exploring the disease pathogenesis.

Methods: Integrated transcriptomics and metabolomics were used to analyze five paired human placentas from patients with severe PE and normal pregnancies. This was followed by further validation of our findings in a publicly available dataset of 173 PE vs. 157 control placentas. In addition, weighted gene coexpression network construction was performed to assess the correlation between genetic alterations and diseases.

Results: We identified 66 and 41 differentially altered metabolites in negative and positive ion modes, respectively, in the PE group compared to the control group, and found 2,560 differentially expressed genes. Several pathways were aberrantly altered in the PE placenta at both the metabolic and transcriptional levels, including steroid hormone biosynthesis, the cAMP signaling pathway, neuroactive ligand–receptor interactions, taste transduction and prion diseases. Additionally, we found 11 differential metabolites and 11 differentially expressed genes involved in the steroid hormone biosynthesis pathway, indicating impaired metabolism of steroid hormones in the PE placenta. Furthermore, we found that CYP11A1, HSD3B2, and HSD17B6 are highly correlated with diseases.

Conclusion: Our findings provide a profile of the dysregulated steroid hormone biosynthesis in PE placenta, we observed a dysregulated cortisol-to-cortisone ratio, testosterone accumulation, decreased testosterone downstream metabolites, impaired production of estrone and estriol, and aberrant hydroxylation and methylation of estradiol. Disorders of placental steroid hormone metabolism might be a consequence or a compensatory change in pathological placentation in PE, which underscores the need to investigate the physiology of steroid hormone metabolites in the etiology of PE.

The impact of different endometrial preparation protocols on obstetric and neonatal complications in frozen-thawed embryo transfer: a retrospective cohort study of 3,458 singleton deliveries

BACKGROUND

Frozen-thawed embryo transfer (FET) is thought to be associated with obstetric and neonatal complications after in vitro fertilization/intracytoplasmic single sperm injection (IVF/ICSI) treatment. The study aimed to determine whether the endometrial preparation protocol is an influencing factor for these complications.

METHODS

We conducted a retrospective cohort study of 3,458 women who had singleton deliveries after IVF/ICSI-FET treatment at the Centre for Reproductive Medicine of Shanghai First Maternity and Infant Hospital between July 2016 and April 2021. The women were divided into three groups according to the endometrial preparation protocols: 2,029 women with programmed cycles, 959 with natural cycles, and 470 with minimal ovarian stimulation cycles. The primary outcomes were the incidence rates of obstetric and neonatal complications, namely, hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), intrahepatic cholestasis of pregnancy (ICP), placenta previa, preterm rupture of membranes (PROM), preterm delivery, postpartum haemorrhage, large for gestational age (LGA), small for gestational age (SGA), and macrosomia.

RESULTS

After adjustments for confounding variables by multivariate logistic regression analysis, the results showed that programmed cycles had an increased risk of HDP (aOR = 1.743; 95% CI, 1.110-2.735; P = 0.016) and LGA (aOR = 1.269; 95% CI, 1.011-1.592; P = 0.040) compared with natural cycles. Moreover, programmed cycles also increased the risk of LGA (aOR = 1.459; 95% CI, 1.083-1.965; P = 0.013) but reduced the risk of SGA (aOR = 0.529; 95% CI, 0.348-0.805; P = 0.003) compared with minimal ovarian stimulation cycles. There were no significant differences between natural cycles and minimal ovarian stimulation cycles.

CONCLUSIONS

During IVF/ICSI-FET treatment, the risk of HDP and LGA was increased in women with programmed cycles. Therefore, for patients with thin endometrium, irregular menstruation or no spontaneous ovulation, minimal ovarian stimulation cycles may be a relatively safer option than programmed cycles.

Pre-eclampsia: a Scoping Review of Risk Factors and Suggestions for Future Research Direction

Abstract

Most of maternal deaths are preventable, and one-quarter of maternal deaths are due to pre-eclampsia and eclampsia. Prenatal screening is essential for detecting and managing pre-eclampsia. However, pre-eclampsia screening is solely based on maternal risk factors and has low (< 5% in the USA) detection rates. This review looks at pre-eclampsia from engineering, public health, and medical points of view. First, pre-eclampsia is defined clinically, and the biological basis of established risk factors is described. The multiple theories behind pre-eclampsia etiology should serve as the scientific basis behind established risk factors for pre-eclampsia; however, African American race does not have sufficient evidence as a risk factor. We then briefly describe predictive statistical models that have been created to improve screening detection rates, which use a combination of biophysical and biochemical biomarkers, as well as aspects of patient medical history as inputs. Lastly, technologies that aid in advancing pre-eclampsia screening worldwide are explored. The review concludes with suggestions for more robust pre-eclampsia research, which includes diversifying study sites, improving biomarker analytical tools, and for researchers to consider studying patients before they become pregnant to improve pre-eclampsia detection rates. Additionally, researchers must acknowledge the systemic racism involved in using race as a risk factor and include qualitative measures in study designs to capture the effects of racism on patients.

Lay Summary

Pre-eclampsia is a pregnancy-specific hypertensive disorder that can affect almost every organ system and complicates 2-8% of pregnancies globally. Here, we focus on the biological basis of the risk factors that have been identified for the condition. African American race currently does not have sufficient evidence as a risk factor and has been poorly studied. Current clinical methods poorly predict a patient's likelihood of developing pre-eclampsia; thus, researchers have made statistical models that are briefly described in this review. Then, low-cost technologies that aid in advancing pre-eclampsia screening are discussed. The review ends with suggestions for research direction to improve pre-eclampsia screening in all settings.Overall, we suggest that the future of pre-eclampsia screening should aim to identify those at risk before they become pregnant. We also suggest that the clinical standard of assessing patient risk solely on patient characteristics needs to be reevaluated, that study locations of pre-eclampsia research need to be expanded beyond a few high-income countries, and that low-cost technologies should be developed to increase access to prenatal screening.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.

Quantitative proteomic analysis of serum-purified exosomes identifies putative pre-eclampsia-associated biomarkers

BACKGROUND

The high incidence of pre-eclampsia, which affects 2-7% of all pregnancies, remains a major health concern. Detection of pre-eclampsia before the appearance of clinical symptoms is essential to allow early intervention, and would benefit from identification of plasma/serum biomarkers to help guide diagnosis and treatment. Liquid biopsy has emerged as a promising source of protein biomarkers that circumvents some of the inherent challenges of proteome-wide analysis of plasma/serum. In this respect, purified exosomes have the added benefit of being carriers of intercellular communication both in physiological and pathological conditions.

METHODS

We compared the protein complement of purified exosomes from three different collections of control and pre-eclamptic serum samples, obtained at the end of the second trimester of pregnancy and at delivery. We employed shotgun label-free proteomics to investigate differential protein expression, which was then validated by targeted proteomics.

RESULTS

We developed a purification method that yielded highly enriched exosome preparations. The presence of specific pregnancy protein markers suggested that a significant proportion of purified exosomes derived from tissues related to pregnancy. Quantitative proteomic analyses allowed us to identify 10, 114 and 98 differentially-regulated proteins in the three sample collections, with a high degree of concordance. Functional analysis suggested that these proteins participate in biological processes related to pre-eclampsia, including angiogenesis, inflammation and cell migration. The differential abundance of 66 proteins was validated by targeted proteomics. Finally, we studied the impact of the pre-eclampsia-associated exosomes in the proteome using an in vitro cellular model.

CONCLUSIONS

We have identified and validated differential exosomal proteins in liquid biopsy of pregnant women that open new possibilities for early detection of pre-eclampsia. Additionally, the functional impact of the proteome composition of purified pre-eclamptic exosomes in target cells provides new information to better understand changes in embryo-maternal interactions and, consequently, the pathogenesis of this disease.

Human Immune System Diseasome Networks and Female Oviductal Microenvironment: New Horizons to be Discovered

Human hypofertility and infertility are two worldwide conditions experiencing nowadays an alarming increase due to a complex ensemble of events. The immune system has been suggested as one of the responsible for some of the etiopathogenic mechanisms involved in these conditions. To shed some light into the strong correlation between the reproductive and immune system, as can be inferred by the several and valuable manuscripts published to date, here we built a network using a useful bioinformatic tool (DisGeNET), in which the key genes involved in the sperm-oviduct interaction were linked. This constitutes an important event related with Human fertility since this interaction, and specially the spermatozoa, represents a not-self entity immunotolerated by the female. As a result, we discovered that some proteins involved in the sperm-oviduct interaction are implicated in several immune system diseases while, at the same time, some immune system diseases could interfere by using different pathways with the reproduction process. The data presented here could be of great importance to understand the involvement of the immune system in fertility reduction in Humans, setting the basis for potential immune therapeutic tools in the near future.

OUP accepted manuscript

Preeclampsia is a pregnancy-specific disease that can have serious effects on the health of both mothers and their offspring. Predicting which women will develop preeclampsia in early pregnancy with high accuracy will allow for improved management. The clinical symptoms of preeclampsia are well recognized, however, the precise molecular mechanisms leading to the disorder are poorly understood. This is compounded by the heterogeneous nature of preeclampsia onset, timing and severity. Indeed a multitude of poorly defined causes including genetic components implicates etiologic factors, such as immune maladaptation, placental ischemia and increased oxidative stress. Large datasets generated by microarray and next-generation sequencing have enabled the comprehensive study of preeclampsia at the molecular level. However, computational approaches to simultaneously analyze the preeclampsia transcriptomic and network data and identify clinically relevant information are currently limited. In this paper, we proposed a control theory method to identify potential preeclampsia-associated genes based on both transcriptomic and network data. First, we built a preeclampsia gene regulatory network and analyzed its controllability. We then defined two types of critical preeclampsia-associated genes that play important roles in the constructed preeclampsia-specific network. Benchmarking against differential expression, betweenness centrality and hub analysis we demonstrated that the proposed method may offer novel insights compared with other standard approaches. Next, we investigated subtype specific genes for early and late onset preeclampsia. This control theory approach could contribute to a further understanding of the molecular mechanisms contributing to preeclampsia.

Clinical tools and biomarkers to predict preeclampsia

Preeclampsia is pregnancy-specific, and significantly contributes to maternal, and perinatal morbidity and mortality worldwide. An effective predictive test for preeclampsia would facilitate early diagnosis, targeted surveillance and timely delivery; however limited options currently exist. A first-trimester screening algorithm has been developed and validated to predict preterm preeclampsia, with poor utility for term disease, where the greatest burden lies. Biomarkers such as sFlt-1 and placental growth factor are also now being used clinically in cases of suspected preterm preeclampsia; their high negative predictive value enables confident exclusion of disease in women with normal results, but sensitivity is modest. There has been a concerted effort to identify potential novel biomarkers that might improve prediction. These largely originate from organs involved in preeclampsia's pathogenesis, including placental, cardiovascular and urinary biomarkers. This review outlines the clinical imperative for an effective test and those already in use and summarises current preeclampsia biomarker research.

Genetic Background of Fetal Growth Restriction

Fetal growth restriction (FGR) is one of the most formidable challenges in present-day antenatal care. Pathological fetal growth is a well-known factor of not only in utero demise in the third trimester, but also postnatal morbidity and unfavorable developmental outcomes, including long-term sequalae such as metabolic diseases, diabetic mellitus or hypertension. In this review, the authors present the current state of knowledge about the genetic disturbances responsible for FGR diagnosis, divided into fetal, placental and maternal causes (including preeclampsia), as well as their impact on prenatal diagnostics, with particular attention on chromosomal microarray (CMA) and noninvasive prenatal testing technique (NIPT).

δ-tocotrienol suppresses the migration and angiogenesis of trophoblasts in preeclampsia and promotes their apoptosis via miR-429/ ZEB1 axis

Preeclampsia (PE) is a severe medical disorder during pregnancy and there has been controversy about the effects of vitamin E on PE. This research intended to explore if δ-tocotrienol (δ-TT), an isomer of vitamin E, could impact PE. Preeclamptic and normal placentas were obtained and total RNA was extracted. The expression of different genes was analyzed through quantitative real-time polymerase chain reaction (qRT-PCR) and Pearson correlation analysis was conducted. After that, HTR-8/SVneo cells (human trophoblasts) were chosen and they were subjected to δ-tocotrienol treatment and then Cell Counting Kit-8 was used to test cell viability. To assess the effects of δ-TT on trophoblasts, wound healing assay and Transwell invasion assay were performed. How miR-429 interacts with ZEB1 was examined via dual luciferase reporter assay. Also, protein expression was evaluated via Western blotting. Our results have shown that δ-TT can impair the viability of trophoblasts and induce their apoptosis. Additionally, it can repress the growth, migration, epithelial-mesenchymal transition (EMT), invasion and angiogenesis in trophoblasts. Mechanistically, δ-TT exerts these effects on trophoblasts via downregulating miR-429 and upregulating ZEB1. Furthermore, miR-429 can bind ZEB1 directly. Clinical sample analysis has revealed that miR-429 expression in preeclamptic placenta is higher than that in normal placenta, but ZEB1 expression in preeclamptic placenta is downregulated. Also, there is a negative association between miR-429 and ZEB1 expression in preeclamptic placentas. These discoveries imply that δ-TT may be hazardous to pregnancy and should not be used in preeclamptic patients. In addition, targeting miR-429 might treat PE.

Early-pregnancy prediction of risk for pre-eclampsia using maternal blood leptin/ceramide ratio: discovery and confirmation

OBJECTIVE

This study aimed to develop a blood test for the prediction of pre-eclampsia (PE) early in gestation. We hypothesised that the longitudinal measurements of circulating adipokines and sphingolipids in maternal serum over the course of pregnancy could identify novel prognostic biomarkers that are predictive of impending event of PE early in gestation.

STUDY DESIGN

Retrospective discovery and longitudinal confirmation.

SETTING

Maternity units from two US hospitals.

PARTICIPANTS

Six previously published studies of placental tissue (78 PE and 95 non-PE) were compiled for genomic discovery, maternal sera from 15 women (7 non-PE and 8 PE) enrolled at ProMedDx were used for sphingolipidomic discovery, and maternal sera from 40 women (20 non-PE and 20 PE) enrolled at Stanford University were used for longitudinal observation.

OUTCOME MEASURES

Biomarker candidates from discovery were longitudinally confirmed and compared in parallel to the ratio of placental growth factor (PlGF) and soluble fms-like tyrosine kinase (sFlt-1) using the same cohort. The datasets were generated by enzyme-linked immunosorbent and liquid chromatography-tandem mass spectrometric assays.

RESULTS

Our discovery integrating genomic and sphingolipidomic analysis identified leptin (Lep) and ceramide (Cer) (d18:1/25:0) as novel biomarkers for early gestational assessment of PE. Our longitudinal observation revealed a marked elevation of Lep/Cer (d18:1/25:0) ratio in maternal serum at a median of 23 weeks' gestation among women with impending PE as compared with women with uncomplicated pregnancy. The Lep/Cer (d18:1/25:0) ratio significantly outperformed the established sFlt-1/PlGF ratio in predicting impending event of PE with superior sensitivity (85% vs 20%) and area under curve (0.92 vs 0.52) from 5 to 25 weeks of gestation.

CONCLUSIONS

Our study demonstrated the longitudinal measurement of maternal Lep/Cer (d18:1/25:0) ratio allows the non-invasive assessment of PE to identify pregnancy at high risk in early gestation, outperforming the established sFlt-1/PlGF ratio test.

Identifying biomarkers for prenatal diagnosis of neural tube defects based on "omics"

Neural tube defects (NTDs) are the most severe birth defects and the main cause of newborn death; posing a great challenge to the affected children, families, and societies. Presently, the clinical diagnosis of NTDs mainly relies on ultrasound images combined with certain indices, such as alpha-fetoprotein levels in the maternal serum and amniotic fluid. Recently, the discovery of additional biomarkers in maternal tissue has presented new possibilities for prenatal diagnosis. Over the past 20 years, "omics" techniques have provided the premise for the study of biomarkers. This review summarizes recent advances in candidate biomarkers for the prenatal diagnosis of fetal NTDs based on omics techniques using maternal biological specimens of different origins, including amniotic fluid, blood, and urine, which may provide a foundation for the early prenatal diagnosis of NTDs.

Screening of differentially expressed proteins in placentas from patients with late-onset preeclampsia

PURPOSE

Preeclampsia (PE) is a severe disease that endangers the safety of mothers and fetuses worldwide. In the absence of specific treatments, more studies on novel predictive and diagnostic biomarkers for PE are required.

EXPERIMENTAL DESIGN

Data-independent acquisition proteomics, with five biological replicates, was used to investigate the protein expression profiles of placental tissues from patients with PE and normal pregnant women.

RESULTS

In total, 52 differentially expressed proteins (DEPs) were identified, 34 of them were upregulated and 18 downregulated. Bioinformatics analyses revealed that PE was associated with multiple GO terms and KEGG pathways. Arginase-1 (ARG1), ferritin light chain (FTL), and RNA cytidine acetyltransferase (NAT10) were identified as hub proteins, which were further validated in placental tissues and maternal plasma by western blot and ELISA.

CONCLUSIONS AND CLINICAL RELEVANCE

FTL expression was significantly lower in the placental tissues and early and late pregnancy plasma of patients with PE compared to that in normal pregnant women. This study is the first to propose that FTL may be a potential predictive and diagnostic biomarker for PE; it provides a proteomics insight for understanding the pathological mechanism of this disease.

Neurologic Sequelae Associated with Hypertensive Disorders of Pregnancy

Hypertensive disorders of pregnancy (HDP) contribute to adverse gene-environment interactions prior to conception and continue throughout pregnancy. Embryonic/fetal brain disorders occur from interactions between genetic susceptibilities interacting with acquired diseases or conditions affecting the maternal/placental fetal (MPF) triad. Trimester-specific pathophysiological mechanisms, such as maternal immune activation and ischemic placental syndrome, contribute to adverse peripartum, neonatal and childhood outcomes. Two diagnostic approaches provide timelier diagnoses over the first 1000 days from conception until two years of age. Horizontal analyses assess the maturation of the triad, neonate and child. Vertical analyses consider systems-biology from genetic, molecular, cellular, tissue through organ networks during each developmental niche. Disease expressions associated with HDP have cumulative adverse effects across the lifespan when subjected to subsequent adverse events. Critical/sensitive periods of developmental neuroplasticity over the first 1000 days are more likely to result in permanent sequelae. Novel diagnostic approaches, beginning during pre-conception, will facilitate the development of effective preventive, rescue and reparative neurotherapeutic strategies in response to HDP-related trimester-specific disease pathways. Public health policies require the inclusion of women's health advocacy during and beyond their reproductive years to reduce sequelae experienced by mothers and their offspring. A lower global burden of neurologic disease from HDP will benefit future generations.

The maternal blood lipidome is indicative of the pathogenesis of severe preeclampsia

Preeclampsia is a pregnancy-specific syndrome characterized by hypertension and proteinuria after 20 weeks of gestation. However, it is not well understood what lipids are involved in the development of this condition, and even less is known how these lipids mediate its formation. To reveal the relationship between lipids and preeclampsia, we conducted lipidomic profiling of maternal sera of 44 severe preeclamptic and 20 healthy pregnant women from a multiethnic cohort in Hawaii. Correlation network analysis showed that oxidized phospholipids have increased intercorrelations and connections in preeclampsia, whereas other lipids, including triacylglycerols, have reduced network correlations and connections. A total of 10 lipid species demonstrate significant changes uniquely associated with preeclampsia but not any other clinical confounders. These species are from the lipid classes of lysophosphatidylcholines, phosphatidylcholines (PCs), cholesteryl esters, phosphatidylethanolamines, lysophosphatidylethanolamines, and ceramides. A random forest classifier built on these lipids shows highly accurate and specific prediction (F1 statistic = 0.94; balanced accuracy = 0.88) of severe preeclampsia, demonstrating their potential as biomarkers for this condition. These lipid species are enriched in dysregulated biological pathways, including insulin signaling, immune response, and phospholipid metabolism. Moreover, causality inference shows that various PCs and lysophosphatidylcholines mediate severe preeclampsia through PC 35:1e. Our results suggest that the lipidome may play a role in the pathogenesis and serve as biomarkers of severe preeclampsia.

Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis

The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed models to evaluate pregnancy status and predict gestational age using omics data from blood biospecimens; however, less invasive methods are desired. Here we propose a model to predict gestational age, using urinary metabolite information. In our prospective cohort study, we collected 2741 urine samples from 187 healthy pregnant women, 23 patients with hypertensive disorders of pregnancy, and 14 patients with spontaneous preterm birth. Using gas chromatography-tandem mass spectrometry, we identified 184 urinary metabolites that showed dynamic systematic changes in healthy pregnant women according to gestational age. A model to predict gestational age during normal pregnancy progression was constructed; the correlation coefficient between actual and predicted weeks of gestation was 0.86. The predicted gestational ages of cases with hypertensive disorders of pregnancy exhibited significant progression, compared with actual gestational ages. This is the first study to predict gestational age in normal and complicated pregnancies by using urinary metabolite information. Minimally invasive urinary metabolomics might facilitate changes in the prediction of gestational age in various clinical settings.

Single cell transcriptome research in human placenta

Human placenta is a complex and heterogeneous organ interfacing between the mother and the fetus that supports fetal development. Alterations to placental structural components are associated with various pregnancy complications. To reveal the heterogeneity among various placenta cell types in normal and diseased placentas, as well as elucidate molecular interactions within a population of placental cells, a new genomics technology called single cell RNA-seq (or scRNA-seq) has been employed in the last couple of years. Here we review the principles of scRNA-seq technology, and summarize the recent human placenta studies at scRNA-seq level across gestational ages as well as in pregnancy complications, such as preterm birth and preeclampsia. We list the computational analysis platforms and resources available for the public use. Lastly, we discuss the future areas of interest for placenta single cell studies, as well as the data analytics needed to accomplish them.

Paired maternal and fetal metabolomics reveal a differential fingerprint in preeclampsia versus fetal growth restriction

Preeclampsia (PE) and fetal growth restriction (FGR) are both placenta-mediated disorders with unclear pathogenesis. Metabolomics of maternal and fetal pairs might help in understanding these disorders. We recruited prospectively pregnancies with normotensive FGR, PE without FGR, PE + FGR and uncomplicated pregnancies as controls. Nuclear magnetic resonance metabolomics were applied on plasma samples collected at delivery. Advanced lipoprotein, glycoprotein and choline profiling was performed using the Liposcale test. The software package Dolphin was used to quantify 24 low-molecular-weight metabolites. Statistical analysis comprised the comparison between each group of complicated pregnancies versus controls, considering 5% false discovery rate correction. Lipid profiles were altered in accordance with the clinical presentation of these disorders. Specifically, PE mothers and FGR fetuses (with or without FGR or PE, respectively) exhibited a pro-atherogenic and pro-inflammatory profile, with higher concentrations of triglycerides, remnant cholesterol (VLDL, IDL) and Glc/GalNAc-linked and lipid-associated glycoproteins compared to controls. Low-molecular-weight metabolites were extensively disturbed in preeclamptic mothers, with or without FGR. Growth restricted fetuses in the presence of PE showed changes in low-molecular-weight metabolites similar to their mothers (increased creatine and creatinine), while normotensive FGR fetuses presented scarce differences, consistent with undernutrition (lower isoleucine). Further research is warranted to clarify maternal and fetal adaptations to PE and FGR.

Secretory products of the corpus luteum and preeclampsia

BACKGROUND

Despite significant advances in our understanding of the pathophysiology of preeclampsia (PE), there are still many unknowns and controversies in the field. Women undergoing frozen-thawed embryo transfer (FET) to a hormonally prepared endometrium have been found to have an unexpected increased risk of PE compared to women who receive embryos in a natural FET cycle. The differences in risk have been hypothesized to be related to the absence or presence of a functioning corpus luteum (CL).

OBJECTIVE AND RATIONALE

To evaluate the literature on secretory products of the CL that could be essential for a healthy pregnancy and could reduce the risk of PE in the setting of FET.

SEARCH METHODS

For this review, pertinent studies were searched in PubMed/Medline (updated June 2020) using common keywords applied in the field of assisted reproductive technologies, CL physiology and preeclampsia. We also screened the complete list of references in recent publications in English (both animal and human studies) on the topics investigated. Given the design of this work as a narrative review, no formal criteria for study selection or appraisal were utilized.

OUTCOMES

The CL is a major source of multiple factors regulating reproduction. Progesterone, estradiol, relaxin and vasoactive and angiogenic substances produced by the CL have important roles in regulating its functional lifespan and are also secreted into the circulation to act remotely during early stages of pregnancy. Beyond the known actions of progesterone and estradiol on the uterus in early pregnancy, their metabolites have angiogenic properties that may optimize implantation and placentation. Serum levels of relaxin are almost undetectable in pregnant women without a CL, which precludes some maternal cardiovascular and renal adaptations to early pregnancy. We suggest that an imbalance in steroid hormones and their metabolites and polypeptides influencing early physiologic processes such as decidualization, implantation, angiogenesis and maternal haemodynamics could contribute to the increased PE risk among women undergoing programmed FET cycles.

WIDER IMPLICATIONS

A better understanding of the critical roles of the secretory products of the CL during early pregnancy holds the promise of improving the efficacy and safety of ART based on programmed FET cycles.

Omics Approaches to Study Formation and Function of Human Placental Syncytiotrophoblast

Proper development of the placenta is vital for pregnancy success. The placenta regulates exchange of nutrients and gases between maternal and fetal blood and produces hormones essential to maintain pregnancy. The placental cell lineage primarily responsible for performing these functions is a multinucleated entity called syncytiotrophoblast. Syncytiotrophoblast is continuously replenished throughout pregnancy by fusion of underlying progenitor cells called cytotrophoblasts. Dysregulated syncytiotrophoblast formation disrupts the integrity of the placental exchange surface, which can be detrimental to maternal and fetal health. Moreover, various factors produced by syncytiotrophoblast enter into maternal circulation, where they profoundly impact maternal physiology and are promising diagnostic indicators of pregnancy health. Despite the multifunctional importance of syncytiotrophoblast for pregnancy success, there is still much to learn about how its formation is regulated in normal and diseased states. ‘Omics’ approaches are gaining traction in many fields to provide a more holistic perspective of cell, tissue, and organ function. Herein, we review human syncytiotrophoblast development and current model systems used for its study, discuss how ‘omics’ strategies have been used to provide multidimensional insights into its formation and function, and highlight limitations of current platforms as well as consider future avenues for exploration.

Urothelial Cancer Associated 1 (UCA1) and miR-193 Are Two Non-coding RNAs Involved in Trophoblast Fusion and Placental Diseases

A bioinformatics screen for non-coding genes was performed from microarrays analyzing on the one hand trophoblast fusion in the BeWo cell model, and on the other hand, placental diseases (preeclampsia and Intra-Uterine Growth Restriction). Intersecting the deregulated genes allowed to identify two miRNA (mir193b and miR365a) and one long non-coding RNA (UCA1) that are pivotal for trophoblast fusion, and deregulated in placental diseases. We show that miR-193b is a hub for the down-regulation of 135 cell targets mainly involved in cell cycle progression and energy usage/nutrient transport. UCA1 was explored by siRNA knock-down in the BeWo cell model. We show that its down-regulation is associated with the deregulation of important trophoblast physiology genes, involved in differentiation, proliferation, oxidative stress, vacuolization, membrane repair and endocrine production. Overall, UCA1 knockdown leads to an incomplete gene expression profile modification of trophoblast cells when they are induced to fuse into syncytiotrophoblast. Then we performed the same type of analysis in cells overexpressing one of the two major isoforms of the STOX1 transcription factor, STOX1A and STOX1B (associated previously to impaired trophoblast fusion). We could show that when STOX1B is abundant, the effects of UCA1 down-regulation on forskolin response are alleviated.

A new approach to the preeclampsia puzzle; MicroRNA-326 in CD4+ lymphocytes might be as a potential suspect

BACKGROUND

Alongside many complications in understanding the etiology of Preeclampsia (PE), several determinants, such as the imbalanced proportion of anti-angiogenic/proangiogenic T-cell subsets, especially CD4⁺ (Th17/Treg), as well as alterations in the expression profile of related cytokines, miRNAs, and transcription factors might have been implicated in PE pathogenesis.

MATERIAL AND METHOD

After sample collection and preparation, CD4⁺ cells were isolated from PE and non-PE pregnant woman and were cultured. Furthermore, analysis such as flow cytometry, real-time PCR, western blotting, and ELISA were performed to assess determinants related to PE manifestation, including sFlt-1, sEng, STAT-3, RORγt, SMAD-7, Foxp3, IL-17, IL-22, Ets-1, and miRNA-326.

RESULTS

Our results showed that the miRNA-326 expression level increased in CD4⁺ Cells and Th17 in PE patients which downregulated Ets-1 expression that acts as a negative control for Th17 development. Furthermore, we showed that the number and expression level of Th17 s and transcription factor RORγt escalated, respectively. While Treg and its related transcription factor (Foxp3) demonstrated a decrease. Flow cytometry analysis illustrated that the Th17/Treg ratio increased in PE. Additionally, we demonstrated that expression and concentration levels of cytokines (IL-17 and IL22) and anti-angiogenic molecules (sEng and sFlt-1) soared in isolated CD4⁺ cells from PE patients, which could be correlated with PE pathogenicity.

CONCLUSION

In conclusion, we comprehensively evaluated immunological factors and molecules involved in PE manifestation. Interestingly, the CD4⁺ T-cell subset could be an extra source of antiangiogenic factors for the maintenance of this hypertension disorder.

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.

Potential Protein Biomarkers for Preeclampsia

To date, the etiology of preeclampsia (PE) has not been clarified and the specific treatment is lacking; hence, early prediction and prevention are very important. Thus, a large number of biomarkers that may be associated with PE have been identified based on proteomics to provide a reference for the prediction of PE and for the understanding of the pathological mechanisms of this disease. This article briefly summarizes the application of proteomics in PE and the potential protein biomarkers to provide a reference for other researchers.

Placental Microarray Profiling Reveals Common mRNA and lncRNA Expression Patterns in Preeclampsia and Intrauterine Growth Restriction

Preeclampsia (PE) and Intrauterine Growth Restriction (IUGR) are major contributors to perinatal morbidity and mortality. These pregnancy disorders are associated with placental dysfunction and share similar pathophysiological features. The aim of this study was to compare the placental gene expression profiles including mRNA and lncRNAs from pregnant women from four study groups: PE, IUGR, PE-IUGR, and normal pregnancy (NP). Gene expression microarray analysis was performed on placental tissue obtained at delivery and results were validated using RTq-PCR. Differential gene expression analysis revealed that the largest transcript variation was observed in the IUGR samples compared to NP (n = 461; 314 mRNAs: 252 up-regulated and 62 down-regulated; 133 lncRNAs: 36 up-regulated and 98 down-regulated). We also detected a group of differentially expressed transcripts shared between the PE and IUGR samples compared to NP (n = 39), including 9 lncRNAs with a high correlation degree (p < 0.05). Functional enrichment of these shared transcripts showed that cytokine signaling pathways, protein modification, and regulation of JAK-STAT cascade are over-represented in both placental ischemic diseases. These findings contribute to the molecular characterization of placental ischemia showing common epigenetic regulation implicated in the pathophysiology of PE and IUGR.