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

Exploring altered free amino acids and metabolites: Insights into the metabolic landscape of preeclampsia

INTRODUCTION

Preeclampsia (PE) is a complex disease that poses a risk for maternal and perinatal morbidity and mortality. This study aimed to investigate the role of maternal serum amino acids (AAs) levels in PE.

MATERIALS AND METHODS

A total of 56 pregnant women (26 with PE and 30 controls) were included in the study. The participants had a confirmed gestational age between 24 and 37 weeks. The mean body mass index (BMI) for the PE group was 33.1 kg/m2, while the control group had a mean BMI of 29.6 kg/m2. AAs levels were quantified, and statistical analyses were performed to identify significant differences between the two groups. Receiver Operating Characteristic (ROC) curve analysis was employed the diagnostic potential of specific AAs.

RESULTS

We observed significantly elevated levels of multiple AAs in the PE group, including citrulline, lysine, ethanolamine, ornithine and histidine. Citrulline exhibited exceptional predictive power for PE with 100.0% sensitivity and specificity at a cutoff of 7.79 µmol/L, reflected in an area under the curve (AUC) of 1.000.

DISCUSSION

Our study highlights the crucial involvement of altered amino acid levels, specifically in the urea cycle, disruptions in lysine and ethanolamine metabolism in PE development. Exploring these changes may reveal new therapeutic targets, providing insights into the disease's molecular mechanisms. Understanding amino acid metabolism in PE not only informs therapeutic strategies but also holds the potential to revolutionize early diagnosis and intervention.

Multi-omics Analysis of Umbilical Cord Hematopoietic Stem Cells from a Multi-ethnic Cohort of Hawaii Reveals the Transgenerational Effect of Maternal Pre-Pregnancy Obesity

Background

Maternal obesity is a health concern that may predispose newborns to a high risk of medical problems later in life. To understand the transgenerational effect of maternal obesity, we conducted a multi-omics study, using DNA methylation and gene expression in the CD34+/CD38-/Lin- umbilical cord blood hematopoietic stem cells (uHSCs) and metabolomics of the cord blood, all from a multi-ethnic cohort (n=72) from Kapiolani Medical Center for Women and Children in Honolulu, Hawaii (collected between 2016 and 2018).

Results

Differential methylation (DM) analysis unveiled a global hypermethylation pattern in the maternal pre-pregnancy obese group (BH adjusted p<0.05), after adjusting for major clinical confounders. Comprehensive functional analysis showed hypermethylation in promoters of genes involved in cell cycle, protein synthesis, immune signaling, and lipid metabolism. Utilizing Shannon entropy on uHSCs methylation, we discerned notably higher quiescence of uHSCs impacted by maternal obesity. Additionally, the integration of multi-omics data-including methylation, gene expression, and metabolomics-provided further evidence of dysfunctions in adipogenesis, erythropoietin production, cell differentiation, and DNA repair, aligning with the findings at the epigenetic level. Furthermore, the CpG sites associated with maternal obesity from these pathways also predicted highly accurately (average AUC = 0.8687) between cancer vs. normal tissues in 14 cancer types in The Cancer Genome Atlas (TCGA).

Conclusions

This study revealed the significant correlation between pre-pregnancy maternal obesity and multi-omics level molecular changes in the uHSCs of offspring, particularly in DNA methylation. Moreover, these maternal obesity epigenetic markers in uHSCs may predispose offspring to higher cancer risks.

Machine learning: a new era for cardiovascular pregnancy physiology and cardio-obstetrics research

The maternal cardiovascular system undergoes functional and structural adaptations during pregnancy and postpartum to support increased metabolic demands of offspring and placental growth, labor, and delivery, as well as recovery from childbirth. Thus, pregnancy imposes physiological stress upon the maternal cardiovascular system, and in the absence of an appropriate response it imparts potential risks for cardiovascular complications and adverse outcomes. The proportion of pregnancy-related maternal deaths from cardiovascular events has been steadily increasing, contributing to high rates of maternal mortality. Despite advances in cardiovascular physiology research, there is still no comprehensive understanding of maternal cardiovascular adaptations in healthy pregnancies. Furthermore, current approaches for the prognosis of cardiovascular complications during pregnancy are limited. Machine learning (ML) offers new and effective tools for investigating mechanisms involved in pregnancy-related cardiovascular complications as well as the development of potential therapies. The main goal of this review is to summarize existing research that uses ML to understand mechanisms of cardiovascular physiology during pregnancy and develop prediction models for clinical application in pregnant patients. We also provide an overview of ML platforms that can be used to comprehensively understand cardiovascular adaptations to pregnancy and discuss the interpretability of ML outcomes, the consequences of model bias, and the importance of ethical consideration in ML use.

Paradoxes: Cholesterol and Hypoxia in Preeclampsia

Preeclampsia, a hypertensive disease of pregnancy of unknown etiology, is intensely studied as a model of cardiovascular disease (CVD) not only due to multiple shared pathologic elements but also because changes that develop over decades in CVD appear and resolve within days in preeclampsia. Those affected by preeclampsia and their offspring experience increased lifetime risks of CVD. At the systemic level, preeclampsia is characterized by increased cellular, membrane, and blood levels of cholesterol; however, cholesterol-dependent signaling, such as canonical Wnt/βcatenin, Hedgehog, and endothelial nitric oxide synthase, is downregulated indicating a cholesterol deficit with the upregulation of cholesterol synthesis and efflux. Hypoxia-related signaling in preeclampsia also appears to be paradoxical with increased Hypoxia-Inducible Factors in the placenta but measurably increased oxygen in maternal blood in placental villous spaces. This review addresses the molecular mechanisms by which excessive systemic cholesterol and deficient cholesterol-dependent signaling may arise from the effects of dietary lipid variance and environmental membrane modifiers causing the cellular hypoxia that characterizes preeclampsia.

The Role of Obesity in the Development of Preeclampsia

PURPOSE OF REVIEW

This comprehensive review provides an in-depth exploration of the complex relationship between obesity and preeclampsia (PE) and emphasizes the clinical implications of this association. It highlights the crucial role of screening tools in assessing individual risk and determining the need for additional antenatal care among women with obesity. The review investigates various markers for identifying the risk of developing PE, while emphasizing the significance of interventions such as exercise, weight management, and a balanced diet in reducing the incidence of preeclampsia and improving outcomes for both mother and fetus.

RECENT FINDINGS

Actually, there is a global pandemic of obesity, particularly among women of childbearing age and pregnant women. PE, which is characterized by maternal hypertension, proteinuria, and complications, affects 2-4% of pregnancies worldwide, posing significant risks to maternal and perinatal health. Women with obesity face an elevated risk of developing PE due to the systemic inflammation resulting from excess adiposity, which can adversely affect placental development. Adipose tissue, rich in proinflammatory cytokines and complement proteins, contributes to the pathogenesis of PE by promoting the expression of antiangiogenic factors in the mother. This review emphasizes the need for appropriate screening, interventions, and a holistic approach to reduce the incidence of preeclampsia and enhance maternal-fetal well-being, thus providing valuable insights into the multifaceted association between obesity and PE.

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.

PPARγ alleviates preeclampsia development by regulating lipid metabolism and ferroptosis

The study aims to explore the effect of PPARγ signaling on ferroptosis and preeclampsia (PE) development. Serum and placental tissue are collected from healthy subjects and PE patients. The PPARγ and Nrf2 decreases in the PE. Rosiglitazone intervention reverses hypoxia-induced trophoblast ferroptosis and decreases lipid synthesis by regulating Nfr2 and SREBP1. Compared to the Hypoxia group, the migratory and invasive abilities enhance after rosiglitazone and ferr1 treatment. Rosiglitazone reduces the effect of hypoxia and erastin. The si-Nrf2 treatment attenuats the effects of rosiglitazone on proliferation, migration, and invasion. The si-Nrf2 does not affect SREBP1 expression. PPARγ agonists alleviates ferroptosis in the placenta of the PE rats. The study confirms that PPARγ signaling and ferroptosis-related indicators were dysregulated in PE. PPARγ/Nrf2 signaling affects ferroptosis by regulating lipid oxidation rather than SREBP1-mediated lipid synthesis. In conclusion, our study find that PPARγ can alleviate PE development by regulating lipid oxidation and ferroptosis.

Investigating genetic links between blood metabolites and preeclampsia

BACKGROUND

Observational studies have revealed that metabolic disorders are closely related to the development of preeclampsia (PE). However, there is still a research gap on the causal role of metabolites in promoting or preventing PE. We aimed to systematically explore the causal association between circulating metabolites and PE.

METHODS

Single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) of 486 blood metabolites (7,824 participants) were extracted as instrumental variables (P < 1 × 10- 5), GWAS summary statistics for PE were obtained from FinnGen consortium (7,212 cases and 194,266 controls) as outcome, and a two-sample Mendelian randomization (MR) analysis was conducted. Inverse variance weighted (IVW) was set as the primary method, with MR-Egger and weighted median as auxiliary methods; the instrumental variable strength and confounding factors were also assessed. Sensitivity analyses including MR-Egger, Cochran's Q test, MR-PRESSO and leave-one-out analysis were performed to test the robustness of the MR results. For significant associations, repeated MR and meta-analysis were performed by another metabolite GWAS (8,299 participants). Furthermore, significantly associated metabolites were subjected to a metabolic pathway analysis.

RESULTS

The instrumental variables for the metabolites ranged from 3 to 493. Primary analysis revealed a total of 12 known (e.g., phenol sulfate, citrulline, lactate and gamma-glutamylglutamine) and 11 unknown metabolites were associated with PE. Heterogeneity and pleiotropy tests verified the robustness of the MR results. Validation with another metabolite GWAS dataset revealed consistency trends in 6 of the known metabolites with preliminary analysis, particularly the finding that genetic susceptibility to low levels of arachidonate (20:4n6) and citrulline were risk factors for PE. The pathway analysis revealed glycolysis/gluconeogenesis and arginine biosynthesis involved in the pathogenesis of PE.

CONCLUSIONS

This study identifies a causal relationship between some circulating metabolites and PE. Our study presented new perspectives on the pathogenesis of PE by integrating metabolomics with genomics, which opens up avenues for more accurate understanding and management of the disease, providing new potential candidate metabolic molecular markers for the prevention, diagnosis and treatment of PE. Considering the limitations of MR studies, further research is needed to confirm the causality and underlying mechanisms of these findings.

Integrating machine learning and nontargeted plasma lipidomics to explore lipid characteristics of premetabolic syndrome and metabolic syndrome

Objective

To identify plasma lipid characteristics associated with premetabolic syndrome (pre-MetS) and metabolic syndrome (MetS) and provide biomarkers through machine learning methods.

Methods

Plasma lipidomics profiling was conducted using samples from healthy individuals, pre-MetS patients, and MetS patients. Orthogonal partial least squares-discriminant analysis (OPLS-DA) models were employed to identify dysregulated lipids in the comparative groups. Biomarkers were selected using support vector machine recursive feature elimination (SVM-RFE), random forest (rf), and least absolute shrinkage and selection operator (LASSO) regression, and the performance of two biomarker panels was compared across five machine learning models.

Results

In the OPLS-DA models, 50 and 89 lipid metabolites were associated with pre-MetS and MetS patients, respectively. Further machine learning identified two sets of plasma metabolites composed of PS(38:3), DG(16:0/18:1), and TG(16:0/14:1/22:6), TG(16:0/18:2/20:4), and TG(14:0/18:2/18:3), which were used as biomarkers for the pre-MetS and MetS discrimination models in this study.

Conclusion

In the initial lipidomics analysis of pre-MetS and MetS, we identified relevant lipid features primarily linked to insulin resistance in key biochemical pathways. Biomarker panels composed of lipidomics components can reflect metabolic changes across different stages of MetS, offering valuable insights for the differential diagnosis of pre-MetS and MetS.

Characteristics of Serum Lipid Metabolism among Women Complicated with Hypertensive Disorders in Pregnancy: A Retrospective Cohort Study in Mainland China

Background

Altered maternal serum lipid metabolism is associated with hypertensive disorders in pregnancy (HDP). However, its range in pregnancy and characteristic among different subgroups of HDPs are unclear.

Methods

Pregnant women with HDP who underwent antenatal care and delivered in Obstetrics and Gynecology Hospital of Fudan University during January 2018 to August 2022 were enrolled. The levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), low-density lipoprotein cholesterol (LDLC), apolipoprotein (Apo)-A, B, and E, free fatty acids (FFA), and small and dense low-density lipoprotein cholesterol (sdLDL) were measured during 4-16 weeks and 28-42 weeks of pregnancy.

Results

A total of 2648 pregnant women were diagnosed with HDP, 1,880 of whom were enrolled for final analysis, including 983 (52.3%) preeclampsia (PE), 676 (36.0%) gestational hypertension (GH), and 221 (11.7%) chronic hypertension (CH). For all HDPs, serum TC, TG, LDLC, HDLC, Apo-A, Apo-B, Apo-E, and sdLDL increased significantly during pregnancy, while FFA decreased significantly. Notably, the levels of TC, LDLC, Apo-B, and sdLDL in PE group were equal to or lower than those in CH group at 4-16 weeks of pregnancy, but increased greatly during pregnancy (P < 0.05).

Conclusions

Maternal serum lipid levels changed through pregnancy among women with HDPs. Women complicated with PE seem to have undergone a more significant serum lipid change compared to those with GH or CH.

Intrauterine growth restriction alters kidney metabolism at the end of nephrogenesis

BACKGROUND

This study investigated the effect of uteroplacental insufficiency (UPI) on renal development by detecting metabolic alterations in the kidneys of rats with intrauterine growth restriction (IUGR).

METHODS

On gestational day 17, pregnant Sprague Dawley rats were selected and allocated randomly to either the IUGR group or the control group. The IUGR group received a protocol involving the closure of bilateral uterine vessels, while the control group underwent a sham surgery. The rat pups were delivered on gestational day 22 by natural means. Pups were randomly recruited from both the control and IUGR groups on the seventh day after birth. The kidneys were surgically removed to conduct Western blot and metabolomic analyses.

RESULTS

IUGR was produced by UPI, as evidenced by the significantly lower body weights of the pups with IUGR compared to the control pups on postnatal day 7. UPI significantly increased the levels of cleaved caspase-3 (p < 0.05) and BAX/Bcl-2 (p < 0.01) in the pups with IUGR. Ten metabolites exhibited statistically significant differences between the groups (q < 0.05). Metabolic pathway enrichment analysis demonstrated statistically significant variations between the groups in the metabolism related to fructose and mannose, amino and nucleotide sugars, and inositol phosphate.

CONCLUSIONS

UPI alters kidney metabolism in growth-restricted newborn rats and induces renal apoptosis. The results of our study have the potential to provide new insights into biomarkers and metabolic pathways that are involved in the kidney changes generated by IUGR.

Ceramides during Pregnancy and Obstetrical Adverse Outcomes

Ceramides are a group of sphingolipids located in the external plasma membrane layer and act as messengers in cellular pathways such as inflammatory processes and apoptosis. Plasma ceramides are biomarkers of cardiovascular disease, type 2 diabetes mellitus, Alzheimer's disease, various autoimmune conditions and cancer. During pregnancy, ceramides play an important role as stress mediators, especially during implantation, delivery and lactation. Based on the current literature, plasma ceramides could be potential biomarkers of obstetrical adverse outcomes, although their role in metabolic pathways under such conditions remains unclear. This review aims to present current studies that examine the role of ceramides during pregnancy and obstetrical adverse outcomes, such as pre-eclampsia, gestational diabetes mellitus and other complications.

Severe preeclampsia is not associated with significant DNA methylation changes but cell proportion changes in the cord blood - caution on the importance of confounding adjustment

Epigenome-wide DNA methylation analysis (EWAS) is an important approach to identify biomarkers for early disease detection and prognosis prediction, yet its results could be confounded by other factors such as cell-type heterogeneity and patient characteristics. In this study, we address the importance of confounding adjustment by examining DNA methylation patterns in cord blood exposed to severe preeclampsia (PE), a prevalent and potentially fatal pregnancy complication. Without such adjustment, a misleading global hypomethylation pattern is obtained. However, after adjusting cell type proportions and patient clinical characteristics, most of the so-called significant CpG methylation changes associated with severe PE disappear. Rather, the major effect of PE on cord blood is through the proportion changes in different cell types. These results are validated using a previously published cord blood DNA methylation dataset, where global hypomethylation pattern was also wrongfully obtained without confounding adjustment. Additionally, several cell types significantly change as gestation progress (eg. granulocyte, nRBC, CD4T, and B cells), further confirming the importance of cell type adjustment in EWAS study of cord blood tissues. Our study urges the community to perform confounding adjustments in EWAS studies, based on cell type heterogeneity and other patient characteristics.

Plasma lipids are dysregulated preceding diagnosis of preeclampsia or delivery of a growth restricted infant

BACKGROUND

Lipids serve as multifunctional metabolites that have important implications for the pregnant mother and developing fetus. Abnormalities in lipids have emerged as potential risk factors for pregnancy diseases, such as preeclampsia and fetal growth restriction. The aim of this study was to assess the potential of lipid metabolites for detection of late-onset preeclampsia and fetal growth restriction.

METHODS

We used a case-cohort of 144 maternal plasma samples at 36 weeks' gestation from patients before the diagnosis of late-onset preeclampsia (n = 22), delivery of a fetal growth restricted infant (n = 55, defined as <5th birthweight centile), gestation-matched controls (n = 72). We performed liquid chromatography-tandem mass spectrometry (LC-QQQ) -based targeted lipidomics to identify 421 lipids, and fitted logistic regression models for each lipid, correcting for maternal age, BMI, smoking, and gestational diabetes.

FINDINGS

Phosphatidylinositol 32:1 (AUC = 0.81) and cholesterol ester 17:1 (AUC = 0.71) best predicted the risk of developing preeclampsia or delivering a fetal growth restricted infant, respectively. Five times repeated five-fold cross validation demonstrated the lipids alone did not out-perform existing protein biomarkers, soluble tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) for the prediction of preeclampsia or fetal growth restriction. However, lipids combined with sFlt-1 and PlGF measurements improved disease prediction.

INTERPRETATION

This study successfully identified 421 lipids in maternal plasma collected at 36 weeks' gestation from participants who later developed preeclampsia or delivered a fetal growth restricted infant. Our results suggest the predictive capacity of lipid measurements for gestational disorders holds the potential to improve non-invasive assessment of maternal and fetal health.

FUNDING

This study was funded by a grant from National Health and Medical Research Council.

A theoretical model of dietary lipid variance as the origin of primary ciliary dysfunction in preeclampsia

Serving as the cell's key interface in communicating with the outside world, primary cilia have emerged as an area of multidisciplinary research interest over the last 2 decades. Although the term "ciliopathy" was first used to describe abnormal cilia caused by gene mutations, recent studies focus on abnormalities of cilia that are found in diseases without clear genetic antecedents, such as obesity, diabetes, cancer, and cardiovascular disease. Preeclampsia, a hypertensive disease of pregnancy, is intensely studied as a model for cardiovascular disease partially due to many shared pathophysiologic elements, but also because changes that develop over decades in cardiovascular disease arise in days with preeclampsia yet resolve rapidly after delivery, thus providing a time-lapse view of the development of cardiovascular pathology. As with genetic primary ciliopathies, preeclampsia affects multiple organ systems. While aspirin delays the onset of preeclampsia, there is no cure other than delivery. The primary etiology of preeclampsia is unknown; however, recent reviews emphasize the fundamental role of abnormal placentation. During normal embryonic development, trophoblastic cells, which arise from the outer layer of the 4-day-old blastocyst, invade the maternal endometrium and establish extensive placental vascular connections between mother and fetus. In primary cilia of trophoblasts, Hedgehog and Wnt/catenin signaling operate upstream of vascular endothelial growth factor to advance placental angiogenesis in a process that is promoted by accessible membrane cholesterol. In preeclampsia, impaired proangiogenic signaling combined with an increase in apoptotic signaling results in shallow invasion and inadequate placental function. Recent studies show primary cilia in preeclampsia to be fewer in number and shortened with functional signaling abnormalities. Presented here is a model that integrates preeclampsia lipidomics and physiology with the molecular mechanisms of liquid-liquid phase separation in model membrane studies and the known changes in human dietary lipids over the last century to explain how changes in dietary lipids might reduce accessible membrane cholesterol and give rise to shortened cilia and defects in angiogenic signaling, which underlie placental dysfunction of preeclampsia. This model offers a possible mechanism for non-genetic dysfunction in cilia and proposes a proof-of-concept study to treat preeclampsia with dietary lipids.

The dynamic inflammatory profile of pregnancy can be monitored using a novel lipid-based mass spectrometry technique

The lipid environment changes throughout pregnancy both physiologically with emergent insulin resistance and pathologically e.g., gestational diabetes mellitus (GDM). Novel mass spectrometry (MS) techniques applied to minimally processed blood might lend themselves to monitoring changing lipid profiles to inform care decisions across pregnancy. In this study we use an intact-sandwich, MALDI-ToF MS method to identify phosphatidylcholine (PC) and lysophosphatidylcholine (LPC) species and calculate their ratio as an indicator of inflammation. Plasma and sera were prepared from venous blood of non-pregnant women (aged 18-40) and pregnant women at 16 weeks, 28 weeks (including GDM-positive women), and 37+ weeks (term) of gestation alongside umbilical cord blood (UCB). Women with a normal menstrual cycle and age-matched men provided finger-prick derived capillary sera at 6 time-points over a month. Serum rather than plasma was preferable for PC/LPC measurement. As pregnancy progresses, an anti-inflammatory phenotype dominates the maternal circulation, evidenced by increasing PC/LPC ratio. In contrast, the PC/LPC ratio of UCB was aligned to that of non-pregnant donors. BMI had no significant effect on the PC/LPC ratio, but GDM-complicated pregnancies had significantly lower PC/LPC at 16 weeks of gestation. To further translate the use of the PC/LPC ratio clinically, the utility of finger-prick blood was evaluated; no significant difference between capillary versus venous serum was found and we revealed the PC/LPC ratio oscillates with the menstrual cycle. Overall, we show that the PC/LPC ratio can be measured simply in human serum and has the potential to be used as a time-efficient and less invasive biomarker of (mal)adaptative inflammation.

Adipokine chemerin overexpression in trophoblasts leads to dyslipidemia in pregnant mice: implications for preeclampsia

BACKGROUND

The adipokine chemerin regulates adipogenesis and the metabolic function of both adipocytes and liver. Chemerin is elevated in preeclamptic women, and overexpression of chemerin in placental trophoblasts induces preeclampsia-like symptoms in mice. Preeclampsia is known to be accompanied by dyslipidemia, albeit via unknown mechanisms. Here, we hypothesized that chemerin might be a contributor to dyslipidemia.

METHODS

Serum lipid fractions as well as lipid-related genes and proteins were determined in pregnant mice with chemerin overexpression in placental trophoblasts and chemerin-overexpressing human trophoblasts. In addition, a phospholipidomics analysis was performed in chemerin-overexpressing trophoblasts.

RESULTS

Overexpression of chemerin in trophoblasts increased the circulating and placental levels of cholesterol rather than triglycerides. It also increased the serum levels of lysophosphatidic acid, high-density lipoprotein cholesterol (HDL-C), and and low-density lipoprotein cholesterol (LDL-C), and induced placental lipid accumulation. Mechanistically, chemerin upregulated the levels of peroxisome proliferator-activated receptor g, fatty acid-binding protein 4, adiponectin, sterol regulatory element-binding protein 1 and 2, and the ratio of phosphorylated extracellular signal-regulated protein kinase (ERK)1/2 / total ERK1/2 in the placenta of mice and human trophoblasts. Furthermore, chemerin overexpression in human trophoblasts increased the production of lysophospholipids and phospholipids, particularly lysophosphatidylethanolamine.

CONCLUSIONS

Overexpression of placental chemerin production disrupts trophoblast lipid metabolism, thereby potentially contributing to dyslipidemia in preeclampsia.

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.

Dissecting the Roles of Lipids in Preeclampsia

Preeclampsia is a multisystem pregnancy disorder that is characterized by different degrees of placental malperfusion, with release of antiangiogenic factors into the circulation, leading to maternal vascular endothelial injury and high blood pressure. As a major cause of maternal and perinatal mortality and morbidity worldwide, once preeclampsia has been diagnosed, there are no curative treatments except for delivery. Lipids serve as ubiquitous and multifunctional metabolites that are integral and essential to many diverse functions on both a cellular and organismal level. Lipid metabolic abnormalities have emerged as potential risk factors for the development and progression of preeclampsia. This review comprehensively examines decades of discovery to illuminate the roles of lipids and dysregulation in the levels of various lipid classes in preeclampsia. In addition, the roles of lipids are summarized to further understand the pathogenic mechanisms of preeclampsia. Overall, the review highlights the promising potential of pathophysiology and lipid-targeting therapeutic strategies in preeclampsia.

Classification of Preeclamptic Placental Extracellular Vesicles Using Femtosecond Laser Fabricated Nanoplasmonic Sensors

Placental extracellular vesicles (EVs) play an essential role in pregnancy by protecting and transporting diverse biomolecules that aid in fetomaternal communication. However, in preeclampsia, they have also been implicated in contributing to disease progression. Despite their potential clinical value, current technologies cannot provide a rapid and effective means of differentiating between healthy and diseased placental EVs. To address this, a fabrication process called laser-induced nanostructuring of SERS-active thin films (LINST) was developed to produce scalable nanoplasmonic substrates that provide exceptional Raman signal enhancement and allow the biochemical fingerprinting of EVs. After validating the performance of LINST substrates with chemical standards, placental EVs from tissue explant cultures were characterized, demonstrating that preeclamptic and normotensive placental EVs have classifiably distinct Raman spectra following the application of advanced machine learning algorithms. Given the abundance of placental EVs in maternal circulation, these findings encourage immediate exploration of surface-enhanced Raman spectroscopy (SERS) of EVs as a promising method for preeclampsia liquid biopsies, while this novel fabrication process will provide a versatile and scalable substrate for many other SERS applications.

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.