Metabolomic determination of pathogenesis of late-onset preeclampsia

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.

Preterm preeclampsia screening using biomarkers: combining phenotypic classifiers into robust prediction models

BACKGROUND

Preeclampsia screening is a critical component of antenatal care worldwide. Currently, the most developed screening test for preeclampsia at 11 to 13 weeks' gestation integrates maternal demographic characteristics and medical history with 3 biomarkers-serum placental growth factor, mean arterial pressure, and uterine artery pulsatility index-to identify approximately 75% of women who develop preterm preeclampsia with delivery before 37 weeks of gestation. It is generally accepted that further improvements to preeclampsia screening require the use of additional biomarkers. We recently reported that the levels of specific metabolites and metabolite ratios are associated with preterm preeclampsia. Notably, for several of these markers, preterm preeclampsia prediction varied according to maternal body mass index class. These findings motivated us to study whether patient classification allowed for combining metabolites with the current biomarkers more effectively to improve prediction of preterm preeclampsia.

OBJECTIVE

This study aimed to investigate whether metabolite biomarkers can improve biomarker-based preterm preeclampsia prediction in 3 screening resource scenarios according to the availability of: (1) placental growth factor, (2) placental growth factor+mean arterial pressure, and (3) placental growth factor+mean arterial pressure+uterine artery pulsatility index.

STUDY DESIGN

This was an observational case-control study, drawn from a large prospective screening study at 11 to 13 weeks' gestation on the prediction of pregnancy complications, conducted at King's College Hospital, London, United Kingdom. Maternal blood samples were also collected for subsequent research studies. We used liquid chromatography-mass spectrometry to quantify levels of 50 metabolites previously associated with pregnancy complications in plasma samples from singleton pregnancies. Biomarker data, normalized using multiples of medians, on 1635 control and 106 preterm preeclampsia pregnancies were available for model development. Modeling was performed using a methodology that generated a prediction model for preterm preeclampsia in 4 consecutive steps: (1) z-normalization of predictors, (2) combinatorial modeling of so-called (weak) classifiers in the unstratified patient set and in discrete patient strata based on body mass index and/or race, (3) selection of classifiers, and (4) aggregation of the selected classifiers (ie, bagging) into the final prediction model. The prediction performance of models was evaluated using the area under the receiver operating characteristic curve, and detection rate at 10% false-positive rate.

RESULTS

First, the predictor development methodology itself was evaluated. The patient set was split into a training set (2/3) and a test set (1/3) for predictor model development and internal validation. A prediction model was developed for each of the 3 different predictor panels, that is, placental growth factor+metabolites, placental growth factor+mean arterial pressure+metabolites, and placental growth factor+mean arterial pressure+uterine artery pulsatility index+metabolites. For all 3 models, the area under the receiver operating characteristic curve in the test set did not differ significantly from that of the training set. Next, a prediction model was developed using the complete data set for the 3 predictor panels. Among the 50 metabolites available for modeling, 26 were selected across the 3 prediction models; 21 contributed to at least 2 out of the 3 prediction models developed. Each time, area under the receiver operating characteristic curve and detection rate were significantly higher with the new prediction model than with the reference model. Markedly, the estimated detection rate with the placental growth factor+mean arterial pressure+metabolites prediction model in all patients was 0.58 (95% confidence interval, 0.49-0.70), a 15% increase (P<.001) over the detection rate of 0.43 (95% confidence interval, 0.33-0.55) estimated for the reference placental growth factor+mean arterial pressure. The same prediction model significantly improved detection in Black (14%) and White (19%) patients, and in the normal-weight group (18.5≤body mass index<25) and the obese group (body mass index≥30), with respectively 19% and 20% more cases detected, but not in the overweight group, when compared with the reference model. Similar improvement patterns in detection rates were found in the other 2 scenarios, but with smaller improvement amplitudes.

CONCLUSION

Metabolite biomarkers can be combined with the established biomarkers of placental growth factor, mean arterial pressure, and uterine artery pulsatility index to improve the biomarker component of early-pregnancy preterm preeclampsia prediction tests. Classification of the pregnant women according to the maternal characteristics of body mass index and/or race proved instrumental in achieving improved prediction. This suggests that maternal phenotyping can have a role in improving the prediction of obstetrical syndromes such as preeclampsia.

Diagnostic Approach to Elevated Liver Function Tests during Pregnancy: A Pragmatic Narrative Review

Liver disease is not uncommon during pregnancy and is associated with increased maternal and fetal/neonatal morbidity and mortality. Physiological changes during pregnancy, including a hyperestrogenic state, increase in circulating plasma volume and/or reduction in splanchnic vascular resistance, and hemostatic imbalance, may mimic or worsen liver disease. For the clinician, it is important to distinguish among the first presentation or exacerbation of chronic liver disease, acute liver disease non-specific to pregnancy, and pregnancy-specific liver disease. This last group classically includes conditions such as hyperemesis gravidarum, intrahepatic cholestasis of pregnancy, liver disorders associated with the pre-eclampsia spectrum, and an acute fatty liver of pregnancy. All of these disorders often share pathophysiological mechanisms, symptoms, and laboratory findings (such as elevated liver enzymes), but a prompt and correct diagnosis is fundamental to guide obstetric conduct, reduce morbidity and mortality, and inform upon the risk of recurrence or development of other chronic diseases later on in life. Finally, the cause of elevated liver enzymes during pregnancy is unclear in up to 30-40% of the cases, and yet, little is known on the causes and mechanisms underlying these alterations, or whether these findings are associated with worse maternal/fetal outcomes. In this narrative review, we aimed to summarize pragmatically the diagnostic work-up and the management of subjects with elevated liver enzymes during pregnancy.

Reversible cerebral vasoconstriction syndrome in the postpartum period: A case report and review of the literature

Reversible cerebral vasoconstriction syndrome (RCVS) is a rare phenomenon that can present in the postpartum period. We show the experience of a 35-year-old patient who presented with headache after an uncomplicated pregnancy and vaginal delivery. She was initially diagnosed with pre-eclampsia, and subsequently with RCVS following discovery of multifocal vascular narrowing on magnetic resonance arteriography (MRA). Verapamil was initiated, and at 1 month there was improvement intracranially, but cervical vertebral arterial narrowing, likely dissection, was discovered. Verapamil was continued and aspirin was initiated. Follow-up imaging 5 months postpartum demonstrated near-complete resolution of previously noted abnormalities, which remained stable at reimaging at 10 months postpartum. In conclusion, the symptoms of RCVS can mimic or coexist with pre-eclampsia. Early intracranial imaging such as MRA can permit timely diagnosis and facilitate appropriate management and follow-up.

Discovery of novel metabolic signatures for early identification of women at risk of developing gestational hypertension

INTRODUCTION

Gestational hypertension (GH) is defined as the presence of systolic blood pressure (BP) ≥ 140 mm Hg and/or diastolic BP ≥ 90 mm Hg, measured at least 4 h apart after 20 weeks of gestation. Early identification of women at high-risk of developing GH could contribute significantly towards improved maternal and fetal outcomes.

OBJECTIVES

To determine early metabolic biomarkers in women with GH as compared with normotensive women.

METHODS

Serum samples were collected from subjects during three stages of their pregnancy: 8-12 weeks, 18-20 weeks and after 28 weeks (< 36 weeks) of gestation and studied using nuclear magnetic resonance (NMR) metabolomics approach. Multivariate and univariate analyses were performed to determine the significantly altered metabolites in GH women.

RESULTS

A total of 10 metabolites, including isoleucine, glutamine, lysine, proline, histidine, phenylalanine, alanine, carnitine, N-acetyl glycoprotein and lactic acid were observed to be significantly downregulated during all pregnancy stages in women with GH as compared with controls. Furthermore, expression of 5 metabolites in the first trimester i.e., phenylalanine [area under the curve (AUC) = 0.745], histidine [AUC = 0.729], proline [AUC = 0.722], lactic acid [AUC = 0.722], and carnitine [AUC = 0.714] exhibited highest potential in discriminating GH from normotensive women.

CONCLUSION

The present study is the first of its kind to identify significantly altered metabolites that have the potential to discriminate between women at risk of developing GH and normotensive women across three trimesters of pregnancy. This opens up the possibility of exploring these metabolites as potential early predictive markers of GH.

Potential biomarkers for late-onset and term preeclampsia: A scoping review

Preeclampsia is a progressive, multisystem pregnancy disorder. According to the time of onset or delivery, preeclampsia has been subclassified into early-onset (&lt;34 weeks) and late-onset (≥34 weeks), or preterm (&lt;37 weeks) and term (≥37 weeks). Preterm preeclampsia can be effectively predicted at 11–13 weeks well before onset, and its incidence can be reduced by preventively using low-dose aspirin. However, late-onset and term preeclampsia are more prevalent than early forms and still lack effective predictive and preventive measures. This scoping review aims to systematically identify the evidence of predictive biomarkers reported in late-onset and term preeclampsia. This study was conducted based on the guidance of the Joanna Briggs Institute (JBI) methodology for scoping reviews. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews (PRISMA-ScR) was used to guide the study. The following databases were searched for related studies: PubMed, Web of Science, Scopus, and ProQuest. Search terms contain “preeclampsia,” “late-onset,” “term,” “biomarker,” or “marker,” and other synonyms combined as appropriate using the Boolean operators “AND” and “OR.” The search was restricted to articles published in English from 2012 to August 2022. Publications were selected if study participants were pregnant women and biomarkers were detected in maternal blood or urine samples before late-onset or term preeclampsia diagnosis. The search retrieved 4,257 records, of which 125 studies were included in the final assessment. The results demonstrate that no single molecular biomarker presents sufficient clinical sensitivity and specificity for screening late-onset and term preeclampsia. Multivariable models combining maternal risk factors with biochemical and/or biophysical markers generate higher detection rates, but they need more effective biomarkers and validation data for clinical utility. This review proposes that further research into novel biomarkers for late-onset and term preeclampsia is warranted and important to find strategies to predict this complication. Other critical factors to help identify candidate markers should be considered, such as a consensus on defining preeclampsia subtypes, optimal testing time, and sample types.

Pre-eclampsia

Pre-eclampsia is a life-threatening disease of pregnancy unique to humans and a leading cause of maternal and neonatal morbidity and mortality. Women who survive pre-eclampsia have reduced life expectancy, with increased risks of stroke, cardiovascular disease and diabetes, while babies from a pre-eclamptic pregnancy have increased risks of preterm birth, perinatal death and neurodevelopmental disability and cardiovascular and metabolic disease later in life. Pre-eclampsia is a complex multisystem disease, diagnosed by sudden-onset hypertension (>20 weeks of gestation) and at least one other associated complication, including proteinuria, maternal organ dysfunction or uteroplacental dysfunction. Pre-eclampsia is found only when a placenta is or was recently present and is classified as preterm (delivery <37 weeks of gestation), term (delivery ≥37 weeks of gestation) and postpartum pre-eclampsia. The maternal syndrome of pre-eclampsia is driven by a dysfunctional placenta, which releases factors into maternal blood causing systemic inflammation and widespread maternal endothelial dysfunction. Available treatments target maternal hypertension and seizures, but the only 'cure' for pre-eclampsia is delivery of the dysfunctional placenta and baby, often prematurely. Despite decades of research, the aetiology of pre-eclampsia, particularly of term and postpartum pre-eclampsia, remains poorly defined. Significant advances have been made in the prediction and prevention of preterm pre-eclampsia, which is predicted in early pregnancy through combined screening and is prevented with daily low-dose aspirin, starting before 16 weeks of gestation. By contrast, the prediction of term and postpartum pre-eclampsia is limited and there are no preventive treatments. Future research must investigate the pathogenesis of pre-eclampsia, in particular of term and postpartum pre-eclampsia, and evaluate new prognostic tests and treatments in adequately powered clinical trials.

The Effects of Pregnancy on Amino Acid Levels and Nitrogen Disposition

Limited data are available on the effects of pregnancy on the maternal metabolome. Therefore, the objective of this study was to use metabolomics analysis to determine pathways impacted by pregnancy followed by targeted confirmatory analysis to provide more powerful conclusions about metabolic alterations during pregnancy. Forty-seven pregnant women, 18-50 years of age were included in this study, with each subject serving as their own control. Plasma samples were collected between 25 and 28 weeks gestation and again ≥3 months postpartum for metabolomics analysis utilizing an HILIC/UHPLC/MS/MS assay with confirmatory targeted specific concentration analysis for 10 of the significantly altered amino acids utilizing an LC/MS assay. Principle component analysis (PCA) on metabolomics data clearly separated pregnant and postpartum groups and identified outliers in a preliminary assessment. Of the 980 metabolites recorded, 706 were determined to be significantly different between pregnancy and postpartum. Pathway analysis revealed three significantly impacted pathways, arginine biosynthesis (p = 2 × 10-5 and FDR = 1 × 10-3), valine, leucine, and isoleucine metabolism (p = 2 × 10-5 and FDR = 2 × 10-3), and xanthine metabolism (p = 4 × 10-5 and FDR = 4 × 10-3). Of these we focused analysis on arginine biosynthesis and branched-chain amino acid (BCAA) metabolism due to their clinical importance and interconnected roles in amino acid metabolism. In the confirmational analysis, 7 of 10 metabolites were confirmed as significant and all 10 confirmed the direction of change of concentrations observed in the metabolomics analysis. The data support an alteration in urea nitrogen disposition and amino acid metabolism during pregnancy. These changes could also impact endogenous nitric oxide production and contribute to diseases of pregnancy. This study provides evidence for changes in both the ammonia-urea nitrogen and the BCAA metabolism taking place during pregnancy.

Associations of Early Pregnancy Metabolite Profiles with Gestational Blood Pressure Development

Blood pressure development plays a major role in both the etiology and prediction of gestational hypertensive disorders. Metabolomics might serve as a tool to identify underlying metabolic mechanisms in the etiology of hypertension in pregnancy and lead to the identification of novel metabolites useful for the prediction of gestational hypertensive disorders. In a population-based, prospective cohort study among 803 pregnant women, liquid chromatography—mass spectrometry was used to determine serum concentrations of amino-acids, non-esterified fatty acids, phospholipids and carnitines in early pregnancy. Blood pressure was measured in each trimester of pregnancy. Information on gestational hypertensive disorders was obtained from medical records. Higher individual metabolite concentrations of the diacyl-phosphatidylcholines and acyl-lysophosphatidylcholines group were associated with higher systolic blood pressure throughout pregnancy (Federal Discovery Rate (FDR)-adjusted p-values < 0.05). Higher concentrations of one non-esterified fatty acid were associated with higher diastolic blood pressure throughout pregnancy (FDR-adjusted p-value < 0.05). Using penalized regression, we identified 12 individual early-pregnancy amino-acids, non-esterified fatty acids, diacyl-phosphatidylcholines and acyl-carnitines and the glutamine/glutamic acid ratio, that were jointly associated with larger changes in systolic and diastolic blood pressure from first to third trimester. These metabolites did not improve the prediction of gestational hypertensive disorders in addition to clinical markers. In conclusion, altered early pregnancy serum metabolite profiles mainly characterized by changes in non-esterified fatty acids and phospholipids metabolites are associated with higher gestational blood pressure throughout pregnancy within the physiological ranges. These findings are important from an etiological perspective and, after further replication, might improve the early identification of women at increased risk of gestational hypertensive disorders.

Prediction of pregnancy-related hypertensive disorders using metabolomics: a systematic review

OBJECTIVE

To determine the accuracy of metabolomics in predicting hypertensive disorders in pregnancy.

DESIGN

Systematic review of observational studies.

DATA SOURCES AND STUDY ELIGIBILITY CRITERIA

An electronic literature search was performed in June 2019 and February 2022. Two researchers independently selected studies published between 1998 and 2022 on metabolomic techniques applied to predict the condition; subsequently, they extracted data and performed quality assessment. Discrepancies were dealt with a third reviewer. The primary outcome was pre-eclampsia. Cohort or case-control studies were eligible when maternal samples were taken before diagnosis of the hypertensive disorder.

STUDY APPRAISAL AND SYNTHESIS METHODS

Data on study design, maternal characteristics, how hypertension was diagnosed, metabolomics details and metabolites, and accuracy were independently extracted by two authors.

RESULTS

Among 4613 initially identified studies on metabolomics, 68 were read in full text and 32 articles were included. Studies were excluded due to duplicated data, study design or lack of identification of metabolites. Metabolomics was applied mainly in the second trimester; the most common technique was liquid-chromatography coupled to mass spectrometry. Among the 122 different metabolites found, there were 23 amino acids and 21 fatty acids. Most of the metabolites were involved with ammonia recycling; amino acid metabolism; arachidonic acid metabolism; lipid transport, metabolism and peroxidation; fatty acid metabolism; cell signalling; galactose metabolism; nucleotide sugars metabolism; lactose degradation; and glycerolipid metabolism. Only citrate was a common metabolite for prediction of early-onset and late-onset pre-eclampsia. Vitamin D was the only metabolite in common for pre-eclampsia and gestational hypertension prediction. Meta-analysis was not performed due to lack of appropriate standardised data.

CONCLUSIONS AND IMPLICATIONS

Metabolite signatures may contribute to further insights into the pathogenesis of pre-eclampsia and support screening tests. Nevertheless, it is mandatory to validate such methods in larger studies with a heterogeneous population to ascertain the potential for their use in clinical practice.

PROSPERO REGISTRATION NUMBER

CRD42018097409.

Proteomics and Metabolomics Profiling of Platelets and Plasma Mediators of Thrombo-Inflammation in Gestational Hypertension and Preeclampsia

Platelets may be pivotal mediators of the thrombotic and coagulopathic complications of preeclampsia (PE), linking inflammation and thrombosis with endothelial and vascular dysfunction. Both PE and gestational hypertension (GH) fall within the spectrum of hypertensive complications of pregnancy, with GH being a risk factor for preeclampsia. However, it is unclear what biomarkers distinguish PE from GH. Using a discovery size cohort, we aimed to characterize specific plasma and platelet thrombo-inflammatory drivers indicative of PE and differentiate PE from GH. We performed multiplex immunoassays, platelet and plasma quantitative proteomics and metabolomics of PE patients, comparing with non-pregnant (NP), healthy pregnant controls (PC) and GH participants. The expression pattern of plasma proteins and metabolites in PE/GH platelets was distinct from that of NP and PC. Whilst procoagulation in PC may be fibrinogen driven, inter-alpha-trypsin inhibitors ITIH2 and ITIH3 are likely mediators of thrombo-inflammation in GH and PE, and fibronectin and S100A8/9 may be major procoagulant agonists in PE only. Also enriched in PE were CCL1 and CCL27 plasma cytokines, and the platelet leucine-rich repeat-containing protein 27 and 42 (LRRC27/42), whose effects on platelets were explored using STRING analysis. Through protein-protein interactions analysis, we generated a new hypothesis for platelets’ contribution to the thrombo-inflammatory states of preeclampsia.

Coenzyme A Restriction as a Factor Underlying Pre-Eclampsia with Polycystic Ovary Syndrome as a Risk Factor

Pre-eclampsia is the most common pregnancy complication affecting 1 in 20 pregnancies, characterized by high blood pressure and signs of organ damage, most often to the liver and kidneys. Metabolic network analysis of published lipidomic data points to a shortage of Coenzyme A (CoA). Gene expression profile data reveal alterations to many areas of metabolism and, crucially, to conflicting cellular regulatory mechanisms arising from the overproduction of signalling lipids driven by CoA limitation. Adverse feedback loops appear, forming sphingosine-1-phosphate (a cause of hypertension, hypoxia and inflammation), cytotoxic isoketovaleric acid (inducing acidosis and organ damage) and a thrombogenic lysophosphatidyl serine. These also induce mitochondrial and oxidative stress, leading to untimely apoptosis, which is possibly the cause of CoA restriction. This work provides a molecular basis for the signs of pre-eclampsia, why polycystic ovary syndrome is a risk factor and what might be done to treat and reduce the risk of disease.

Identification of Biomarkers for Preeclampsia Based on Metabolomics

Background

Preeclampsia (PE) is a significant cause of maternal and neonatal morbidity and mortality worldwide. However, the pathogenesis of PE is unclear and reliable early diagnostic methods are still lacking. The purpose of this review is to summarize potential metabolic biomarkers and pathways of PE, which might facilitate risk prediction and clinical diagnosis, and obtain a better understanding of specific metabolic mechanisms of PE.

Methods

This review included human metabolomics studies related to PE in the PubMed, Google Scholar, and Web of Science databases from January 2000 to November 2021. The reported metabolic biomarkers were systematically examined and compared. Pathway analysis was conducted through the online software MetaboAnalyst 5.0.

Results

Forty-one human studies were included in this systematic review. Several metabolites, such as creatinine, glycine, L-isoleucine, and glucose and biomarkers with consistent trends (decanoylcarnitine, 3-hydroxyisovaleric acid, and octenoylcarnitine), were frequently reported. In addition, eight amino acid metabolism-related, three carbohydrate metabolism-related, one translation-related and one lipid metabolism-related pathways were identified. These biomarkers and pathways, closely related to renal dysfunction, insulin resistance, lipid metabolism disorder, activated inflammation, and impaired nitric oxide production, were very likely to contribute to the progression of PE.

Conclusion

This study summarized several metabolites and metabolic pathways, which may be associated with PE. These high-frequency differential metabolites are promising to be biomarkers of PE for early diagnosis, and the prominent metabolic pathway may provide new insights for the understanding of the pathogenesis of PE.

Maternal Amino Acid Status in Severe Preeclampsia: A Cross-Sectional Study

Introduction: Preeclampsia has been one of the leading causes of maternal death in Indonesia. It is postulated that its relationship with oxidative stress may be the underlying pathology of the disease. Nutrients and amino acids have been suggested as a scavenger for oxygen-free radicals. No previous study regarding the amino acid status in preeclampsia has been conducted in women in Indonesia. Methods: This was a cross-sectional study of a total of 64 pregnant women, 30 with normal pregnancy and 34 with severe preeclampsia. Data were obtained in Cipto Mangunkusumo National Referral Hospital in Jakarta from July to December 2020. Maternal blood samples were taken during or soon after delivery. Amino acid levels were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Bivariate analysis was then performed. Results: We identified 19 different levels of amino acids in this study. Four amino acids that were elevated in the preeclampsia group were phenylalanine, serine, glycine, and glutamate. Serine (331.55 vs. 287.43; p = 0.03), glycine (183.3 vs. 234.35, p = 0.03), and glutamate levels (102.23 vs. 160.70, p = 0.000) were higher in preeclamptic patients. While in the essential amino acids group, phenylalanine levels (71.5 vs. 85.5, p = 0.023) were higher, and methionine levels (16.3 vs. 12.9, p = 0.022) were lower in preeclamptic patients. Conclusions: These findings suggest that severe preeclampsia had differences in concentration of some amino acids compared to normal pregnancy. Glutamate and methionine were associated with preeclampsia. Furthermore, a more detailed study regarding amino acids in the pathomechanism of preeclampsia is suggested.

Metformin Corrects Glucose Metabolism Reprogramming and NLRP3 Inflammasome-Induced Pyroptosis via Inhibiting the TLR4/NF-κB/PFKFB3 Signaling in Trophoblasts: Implication for a Potential Therapy of Preeclampsia

NOD-like receptor family, pyrin domain-containing protein 3 (NLRP3) inflammasome-mediated pyroptosis is a crucial event in the preeclamptic pathogenesis, tightly linked with the uteroplacental TLR4/NF-κB signaling. Trophoblastic glycometabolism reprogramming has now been noticed in the preeclampsia pathogenesis, plausibly modulated by the TLR4/NF-κB signaling as well. Intriguingly, cellular pyroptosis and metabolic phenotypes may be inextricably linked and interacted. Metformin (MET), a widely accepted NF-κB signaling inhibitor, may have therapeutic potential in preeclampsia while the underlying mechanisms remain unclear. Herein, we investigated the role of MET on trophoblastic pyroptosis and its relevant metabolism reprogramming. The safety of pharmacologic MET concentration to trophoblasts was verified at first, which had no adverse effects on trophoblastic viability. Pharmacological MET concentration suppressed NLRP3 inflammasome-induced pyroptosis partly through inhibiting the TLR4/NF-κB signaling in preeclamptic trophoblast models induced via low-dose lipopolysaccharide. Besides, MET corrected the glycometabolic reprogramming and oxidative stress partly via suppressing the TLR4/NF-κB signaling and blocking transcription factor NF-κB1 binding on the promoter PFKFB3, a potent glycolytic accelerator. Furthermore, PFKFB3 can also enhance the NF-κB signaling, reduce NLRP3 ubiquitination, and aggravate pyroptosis. However, MET suppressed pyroptosis partly via inhibiting PFKFB3 as well. These results provided that the TLR4/NF-κB/PFKFB3 pathway may be a novel link between metabolism reprogramming and NLRP3 inflammasome-induced pyroptosis in trophoblasts. Further, MET alleviates the NLRP3 inflammasome-induced pyroptosis, which partly relies on the regulation of TLR4/NF-κB/PFKFB3-dependent glycometabolism reprogramming and redox disorders. Hence, our results provide novel insights into the pathogenesis of preeclampsia and propose MET as a potential therapy.

Preeclampsia: From Cellular Wellness to Inappropriate Cell Death, and the Roles of Nutrition

Preeclampsia is one of the most common obstetrical complications worldwide. The pathomechanism of this disease begins with abnormal placentation in early pregnancy, which is associated with inappropriate decidualization, vasculogenesis, angiogenesis, and spiral artery remodeling, leading to endothelial dysfunction. In these processes, appropriate cellular deaths have been proposed to play a pivotal role, including apoptosis and autophagy. The proper functioning of these physiological cell deaths for placentation depends on the wellbeing of the trophoblasts, affected by the structural and functional integrity of each cellular component including the cell membrane, mitochondria, endoplasmic reticulum, genetics, and epigenetics. This cellular wellness, which includes optimal cellular integrity and function, is heavily influenced by nutritional adequacy. In contrast, nutritional deficiencies may result in the alteration of plasma membrane, mitochondrial dysfunction, endoplasmic reticulum stress, and changes in gene expression, DNA methylation, and miRNA expression, as well as weakened defense against environmental contaminants, hence inducing a series of inappropriate cellular deaths such as abnormal apoptosis and necrosis, and autophagy dysfunction and resulting in abnormal trophoblast invasion. Despite their inherent connection, the currently available studies examined the functions of each organelle, the cellular death mechanisms and the nutrition involved, both physiologically in the placenta and in preeclampsia, separately. Therefore, this review aims to comprehensively discuss the relationship between each organelle in maintaining the physiological cell death mechanisms and the nutrition involved, and the interconnection between the disruptions in the cellular organelles and inappropriate cell death mechanisms, resulting in poor trophoblast invasion and differentiation, as seen in preeclampsia.

Metabolomics Analysis of Amniotic Fluid in Euploid Foetuses with Thickened Nuchal Translucency by Gas Chromatography-Mass Spectrometry

Persistence of a fetal thickened nuchal translucency (NT), one of the most sensitive and specific individual markers of fetal disorders, is strongly correlated with the possibility of a genetic syndrome, congenital infections, or other malformations. Thickened NT can also be found in normal pregnancies. Several of its pathophysiological aspects still remain unexplained. Metabolomics could offer a fresh opportunity to explore maternal-foetal metabolism in an effort to explain its physiological and pathological mechanisms. For this prospective case-control pilot study, thirty-nine samples of amniotic fluids were collected, divisible into 12 euploid foetuses with an enlarged nuchal translucency (>NT) and 27 controls (C). Samples were analyzed using gas chromatography mass spectrometry. Multivariate and univariate statistical analyses were performed to find a specific metabolic pattern of >NT class. The correlation between the metabolic profile and clinical parameters was evaluated (NT showed an R2 = 0.75, foetal crown-rump length showed R2 = 0.65, pregnancy associated plasma protein-A showed R2 = 0.60). Nine metabolites significantly differing between >NT foetuses and C were detected: 2-hydroxybutyric acid, 3-hydroxybutyric, 1,5 Anydro-Sorbitol, cholesterol, erythronic acid, fructose, malic acid, threitol, and threonine, which were linked to altered pathways involved in altered energetic pathways. Through the metabolomics approach, it was possible to identify a specific metabolic fingerprint of the fetuses with >NT.

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.

Metabolomics in Prenatal Medicine: A Review

Pregnancy is a complicated and insidious state with various aspects to consider, including the well-being of the mother and child. Developing better non-invasive tests that cover a broader range of disorders with lower false-positive rates is a fundamental necessity in the prenatal medicine field, and, in this sense, the application of metabolomics could be extremely useful. Metabolomics measures and analyses the products of cellular biochemistry. As a biomarker discovery tool, the integrated holistic approach of metabolomics can yield new diagnostic or therapeutic approaches. In this review, we identify and summarize prenatal metabolomics studies and identify themes and controversies. We conducted a comprehensive search of PubMed and Google Scholar for all publications through January 2020 using combinations of the following keywords: nuclear magnetic resonance, mass spectrometry, metabolic profiling, prenatal diagnosis, pregnancy, chromosomal or aneuploidy, pre-eclampsia, fetal growth restriction, pre-term labor, and congenital defect. Metabolite detection with high throughput systems aided by advanced bioinformatics and network analysis allowed for the identification of new potential prenatal biomarkers and therapeutic targets. We took into consideration the scientific papers issued between the years 2000-2020, thus observing that the larger number of them were mainly published in the last 10 years. Initial small metabolomics studies in perinatology suggest that previously unidentified biochemical pathways and predictive biomarkers may be clinically useful. Although the scientific community is considering metabolomics with increasing attention for the study of prenatal medicine as well, more in-depth studies would be useful in order to advance toward the clinic world as the obtained results appear to be still preliminary. Employing metabolomics approaches to understand fetal and perinatal pathophysiology requires further research with larger sample sizes and rigorous testing of pilot studies using various omics and traditional hypothesis-driven experimental approaches.

Untargeted analysis of first trimester serum to reveal biomarkers of pregnancy complications: a case-control discovery phase study

Understanding of causal biology and predictive biomarkers are lacking for hypertensive disorders of pregnancy (HDP) and preterm birth (PTB). First-trimester serum specimens from 51 cases of HDP, including 18 cases of pre-eclampsia (PE) and 33 cases of gestational hypertension (GH); 53 cases of PTB; and 109 controls were obtained from the Global Alliance to Prevent Prematurity and Stillbirth repository. Metabotyping was conducted using liquid chromatography high resolution mass spectroscopy and nuclear magnetic resonance spectroscopy. Multivariable logistic regression was used to identify signals that differed between groups after controlling for confounders. Signals important to predicting HDP and PTB were matched to an in-house physical standards library and public databases. Pathway analysis was conducted using GeneGo MetaCore. Over 400 signals for endogenous and exogenous metabolites that differentiated cases and controls were identified or annotated, and models that included these signals produced substantial improvements in predictive power beyond models that only included known risk factors. Perturbations of the aminoacyl-tRNA biosynthesis, L-threonine, and renal secretion of organic electrolytes pathways were associated with both HDP and PTB, while pathways related to cholesterol transport and metabolism were associated with HDP. This untargeted metabolomics analysis identified signals and common pathways associated with pregnancy complications.

Revisiting preeclampsia: a metabolic disorder of the placenta

Preeclampsia (PE) is a leading cause of maternal and neonatal mortality and morbidity worldwide, impacting the long-term health of both mother and offspring. PE has long been characterized by deficient trophoblast invasion into the uterus and consequent placental hypoperfusion, yet the upstream causative factors and effective interventional targets for PE remain unknown. Alterations in the metabolism of preeclamptic placentas are thought to result from placental ischemia, while disturbances of the metabolism and of metabolites in PE pathogenesis are largely ignored. In fact, as one of the largest fetal organs at birth, the placenta consumes a considerable amount of glucose and fatty acid. Increasing evidence suggests glucose and fatty acid exist as energy substrates and regulate placental development through bioactive derivates. Moreover, recent findings have revealed that the placental metabolism adapts readily to environmental changes, altering its response to nutrients and endocrine signals; this adaptability optimizes pregnancy outcomes by diversifying available carbon sources for energy production, hormone synthesis, angiogenesis, immune activation, and tolerance, and fetoplacental growth. These observations raise the possibility that carbohydrate and lipid metabolism abnormalities play a role in both the etiology and clinical progression of PE, sparking a renewed interest in the interrelationship between PE and metabolic dysregulation. This review will focus on key metabolic substrates and regulatory molecules in the placenta and aim to provide novel insights with respect to the metabolism's role in modulating placental development and functions. Further investigations from this perspective are poised to decipher the etiology of PE and suggest potential therapies.

Regulation of maternal-fetal metabolic communication

Pregnancy may be the most nutritionally sensitive stage in the life cycle, and improved metabolic health during gestation and early postnatal life can reduce the risk of chronic disease in adulthood. Successful pregnancy requires coordinated metabolic, hormonal, and immunological communication. In this review, maternal-fetal metabolic communication is defined as the bidirectional communication of nutritional status and metabolic demand by various modes including circulating metabolites, endocrine molecules, and other secreted factors. Emphasis is placed on metabolites as a means of maternal-fetal communication by synthesizing findings from studies in humans, non-human primates, domestic animals, rabbits, and rodents. In this review, fetal, placental, and maternal metabolic adaptations are discussed in turn. (1) Fetal macronutrient needs are summarized in terms of the physiological adaptations in place to ensure their proper allocation. (2) Placental metabolite transport and maternal physiological adaptations during gestation, including changes in energy budget, are also discussed. (3) Maternal nutrient limitation and metabolic disorders of pregnancy serve as case studies of the dynamic nature of maternal-fetal metabolic communication. The review concludes with a summary of recent research efforts to identify metabolites, endocrine molecules, and other secreted factors that mediate this communication, with particular emphasis on serum/plasma metabolomics in humans, non-human primates, and rodents. A better understanding of maternal-fetal metabolic communication in health and disease may reveal novel biomarkers and therapeutic targets for metabolic disorders of pregnancy.

Targeted metabolomics highlights perturbed metabolism in the brain of autism spectrum disorder sufferers

INTRODUCTION

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by deficiencies in social interactions and communication, combined with restricted and repetitive behavioral issues.

OBJECTIVES

As little is known about the etiopathophysiology of ASD and early diagnosis is relatively subjective, we aim to employ a targeted, fully quantitative metabolomics approach to biochemically profile post-mortem human brain with the overall goal of identifying metabolic pathways that may have been perturbed as a result of the disease while uncovering potential central diagnostic biomarkers.

METHODS

Using a combination of ¹H NMR and DI/LC-MS/MS we quantitatively profiled the metabolome of the posterolateral cerebellum from post-mortem human brain harvested from people who suffered with ASD (n = 11) and compared them with age-matched controls (n = 10).

RESULTS

We accurately identified and quantified 203 metabolites in post-mortem brain extracts and performed a metabolite set enrichment analyses identifying 3 metabolic pathways as significantly perturbed (p < 0.05). These include Pyrimidine, Ubiquinone and Vitamin K metabolism. Further, using a variety of machine-based learning algorithms, we identified a panel of central biomarkers (9-hexadecenoylcarnitine (C16:1) and the phosphatidylcholine PC ae C36:1) capable of discriminating between ASD and controls with an AUC = 0.855 with a sensitivity and specificity equal to 0.80 and 0.818, respectively.

CONCLUSION

For the first time, we report the use of a multi-platform metabolomics approach to biochemically profile brain from people with ASD and report several metabolic pathways which are perturbed in the diseased brain of ASD sufferers. Further, we identified a panel of biomarkers capable of distinguishing ASD from control brains. We believe that these central biomarkers may be useful for diagnosing ASD in more accessible biomatrices.

Early Pregnancy Serum Metabolite Profiles Associated with Hypertensive Disorders of Pregnancy in African American Women: A Pilot Study

Hypertensive disorders of pregnancy (HDP) are the most common cardiometabolic complications of pregnancy, affecting nearly 10% of US pregnancies and contributing substantially to maternal and infant morbidity and mortality. In the US, women of African American race are at increased risk for HDP. Early biomarkers that reliably identify women at risk for HDP remain elusive, yet are essential for the early identification and targeting of interventions to improve maternal and infant outcomes. We employed high-resolution metabolomics (HRM) to identify metabolites and metabolic pathways that were altered in early (8-14 weeks) gestation serum samples of pregnant African American women who developed HDP after 20 weeks' gestation (n = 20)-either preeclampsia (PE; n = 11) or gestational hypertension (gHTN; n = 9)-compared to those who delivered full term without complications (n = 80). We found four metabolic pathways that were significantly (p < 0.05) altered in women who developed PE and five pathways that were significantly (p < 0.05) altered in women who developed gHTN compared to women who delivered full term without complications. We also found that four specific metabolites (p < 0.05) were distinctly upregulated (retinoate, kynurenine) or downregulated (SN-glycero-3-phosphocholine, 2'4'-dihydroxyacetophenone) in women who developed PE compared to gHTN. These findings support that there are systemic metabolic disruptions that are detectable in early pregnancy (8-14 weeks of gestation) among pregnant African American women who develop PE and gHTN. Furthermore, the early pregnancy metabolic disruptions associated with PE and gHTN are distinct, implying they are unique entities rather than conditions along a spectrum of the same disease process despite the common clinical feature of high blood pressure.

A review of omics approaches to study preeclampsia

Preeclampsia is a medical condition affecting 5-10% of pregnancies. It has serious effects on the health of the pregnant mother and developing fetus. While possible causes of preeclampsia are speculated, there is no consensus on its etiology. The advancement of big data and high-throughput technologies enables to study preeclampsia at the new and systematic level. In this review, we first highlight the recent progress made in the field of preeclampsia research using various omics technology platforms, including epigenetics, genome-wide association studies (GWAS), transcriptomics, proteomics and metabolomics. Next, we integrate the results in individual omic level studies, and show that despite the lack of coherent biomarkers in all omics studies, inhibin is a potential preeclamptic biomarker supported by GWAS, transcriptomics and DNA methylation evidence. Using network analysis on the biomarkers of all the literature reviewed here, we identify four striking sub-networks with clear biological functions supported by previous molecular-biology and clinical observations. In summary, omics integration approach offers the promise to understand molecular mechanisms in preeclampsia.

Quantitative methods for metabolomic analyses evaluated in the Children's Health Exposure Analysis Resource (CHEAR)

With advances in technologies that facilitate metabolome-wide analyses, the incorporation of metabolomics in the pursuit of biomarkers of exposure and effect is rapidly evolving in population health studies. However, many analytic approaches are limited in their capacity to address high-dimensional metabolomics data within an epidemiologic framework, including the highly collinear nature of the metabolites and consideration of confounding variables. In this Children's Health Exposure Analysis Resource (CHEAR) network study, we showcase various analytic approaches that are established as well as novel in the field of metabolomics, including univariate single metabolite models, least absolute shrinkage and selection operator (LASSO), random forest, weighted quantile sum (WQS_RS) regression, exploratory factor analysis (EFA), and latent class analysis (LCA). Here, in a Bangladeshi birth cohort (n = 199), we illustrate research questions that can be addressed by each analytic method in the assessment of associations between cord blood metabolites (¹H NMR measurements) and birth anthropometric measurements (birth weight and head circumference).

Metabolomics Identifies Placental Dysfunction and Confirms Flt-1 (FMS-Like Tyrosine Kinase Receptor 1) Biomarker Specificity

Clinical end-stage parameters define the pregnancy disorders preeclampsia and fetal growth restriction while classification of the underlying placental dysfunction is missing and urgently needed. Flt-1 (FMS-like tyrosine kinase receptor 1) is the most promising placenta-derived predictive biomarker for preeclampsia. We aimed to classify placental dysfunction in preeclampsia and fetal growth restriction at delivery by metabolic profiling and authenticate the biomarker Flt-1 for placental dysfunction. We studied 143 pregnancies with or without preeclampsia and/or fetal growth restriction delivered by cesarean section. Metabolic placenta profiles were created by high-resolution magic angle spinning nuclear magnetic resonance spectroscopy and the resulting placental phenotypes obtained by hierarchical clustering. Placental Flt-1 expression (membrane-bound and soluble isoforms combined) and maternal serum Flt-1 expression (soluble isoforms) were analyzed by immunohistochemistry and ELISA, respectively. We identified 3 distinct placenta groups by 21 metabolites and diagnostic outcome parameters; normal placentas, moderate placental dysfunction, and severe placental dysfunction. Increased placental Flt-1 was associated with severe placental dysfunction, and increased serum Flt-1 was associated with moderate and severe placental dysfunction. The preeclamptic pregnancies with and without placental dysfunction could be distinguished by 5 metabolites and placental Flt-1. Placental Flt-1 alone could separate normal pregnancies with and without placental dysfunction. In conclusion, metabolomics could classify placental dysfunction and provide information not identified by traditional diagnostics and metabolites with biomarker potential were identified. Flt-1 was confirmed as precision biomarker for placental dysfunction, substantiating its usefulness for identification of high-risk pregnancies for preeclampsia and fetal growth restriction with placental involvement.

Second trimester inflammatory and metabolic markers in women delivering preterm with and without preeclampsia

OBJECTIVE

Inflammatory and metabolic pathways are implicated in preterm birth and preeclampsia. However, studies rarely compare second trimester inflammatory and metabolic markers between women who deliver preterm with and without preeclampsia.

STUDY DESIGN

A sample of 129 women (43 with preeclampsia) with preterm delivery was obtained from an existing population-based birth cohort. Banked second trimester serum samples were assayed for 267 inflammatory and metabolic markers. Backwards-stepwise logistic regression models were used to calculate odds ratios.

RESULTS

Higher 5-α-pregnan-3β,20α-diol disulfate, and lower 1-linoleoylglycerophosphoethanolamine and octadecanedioate, predicted increased odds of preeclampsia.

CONCLUSIONS

Among women with preterm births, those who developed preeclampsia differed with respect metabolic markers. These findings point to potential etiologic underpinnings for preeclampsia as a precursor to preterm birth.

Application of metabolomics to preeclampsia diagnosis

Preeclampsia is a multifactorial disorder defined by hypertension and increased urinary protein excretion during pregnancy. It is a significant cause of maternal and neonatal deaths worldwide. Despite various research efforts to clarify pathogenies of preeclampsia and predict this disease before beginning of symptoms, the pathogenesis of preeclampsia is unclear. Early prediction and diagnosis of women at risk of preeclampsia has not markedly improved. Therefore, the objective of this study was to perform a review on metabolomic articles assessing predictive and diagnostic biomarkers of preeclampsia. Four electronic databases including PubMed/Medline, Web of Science, Sciencedirect, and Scopus were searched to identify studies of preeclampsia in humans using metabolomics from inception to March 2018. Twenty-one articles in a variety of biological specimens and analytical platforms were included in the present review. Metabolite profiles may assist in the diagnosis of preeclampsia and discrimination of its subtypes. Lipids and their related metabolites were the most generally detected metabolites. Although metabolomic biomarkers of preeclampsia are not routinely used, this review suggests that metabolomics has the potential to be developed into a clinical tool for preeclampsia diagnosis and could contribute to an improved understanding of disease mechanisms.

ABBREVIATIONS

PE: preeclampsia; sFlt-1: soluble FMS-like tyrosine kinase-1; PlGF: placental growth factor; GC-MS: gas chromatography-mass spectrometry; LC-MS: liquid chromatography-mass spectrometry; NMR: nuclear magnetic resonance spectroscopy; HMDB: human metabolome database; RCT: randomized control trial; e-PE: early-onset PE; l-PE: late-onset PE; PLS-DA: partial least-squares-discriminant analysis; CRL: crown-rump length; UtPI: uterine artery Doppler pulsatility index; BMI: body mass index; MAP: mean arterial pressure; OS: oxidative stress; PAPPA: plasma protein A; FTIR: Fourier transform infrared; BCAA: branched chain amino acids; Arg: arginine; NO: nitric oxide.

The metabolic role of LncZBTB39-1:2 in the trophoblast mobility of preeclampsia

Preeclampsia is characterized by new onset of hypertension and proteinuria after 20 weeks' gestation and is a leading cause of maternal and neonatal morbidity and mortality. The pathogenesis of preeclampsia is often associated with aberrant trophoblast function that leads to shallow placental implantation. However, the exact underlying mechanisms remain unclear. Placental LncZBTB39-1:2 expression level was investigated in 20 healthy placentae and 20 placentae with preeclampsia using qRT-PCR, and the metabolic profile of trophoblasts overexpressing LncZBTB39-1:2 in vitro was analysed using gas chromatography-mass spectrometry (GC-MS). In this study, we found that the expression of LncZBTB39-1:2 was significantly higher in preeclamptic placentae than in healthy placentae. Our metabolomics results have shown that tricarboxylic acid cycle intermediates and metabolites related to carbohydrate metabolism were decreased with the overexpression of LncZBTB39-1:2 in HTR8/SVneo cells. These findings were validated by detecting a lower level of intracellular ATP in HTR8/Vneo cells. Furthermore, the migration of HTR8/SVneo cells was compromised when cells were transfected with a plasmid encompassing LncZBTB39-1:2 overexpression. From these results, we conclude that abnormal levels of LncZBTB39-1:2 expression might lead to aberrant conditions in HTR-8/SVneo trophoblast cells. Aberrant conditions might be associated with dysregulated trophoblast migration and subsequent failure of uterine spiral artery remodelling, a pathogenesis recognised as a contributing factor in the aetiology of preeclampsia.