Metabolomic identification of placental alterations in fetal growth restriction

Acetyl-CoA metabolism maintains histone acetylation for syncytialization of human placental trophoblast stem cells

During pregnancy, placental-fetal nutrient allocation is crucial for fetal and maternal health. However, the regulatory mechanisms for nutrient metabolism and allocation in placental trophoblasts have remained unclear. Here, we used human first-trimester placenta samples and human trophoblast stem cells (hTSCs) to discover that glucose metabolism is highly active in hTSCs and cytotrophoblasts, but during syncytialization, it decreases to basal levels, remaining necessary for fueling acetyl-CoA and differentiation potential. Acetate supplementation could rescue syncytiotrophoblast fusion from glycolysis deficiency by replenishing acetyl-CoA and maintaining histone acetylation, thus rescuing the activation of syncytialization genes. Even brief glycolysis deficiency could permanently inhibit differentiation potential and promote inflammation, which could also be permanently rescued by brief acetate supplementation in vivo. These results suggest that hTSCs retain only basal glycolytic acetyl-CoA metabolism during syncytialization to regulate cell fates via nutrient-responsive histone acetylation, with implications for our understanding of the balance between placental and fetal nutrition.

Association of cord plasma metabolites with birth weight: results from metabolomic and lipidomic studies of discovery and validation cohorts

OBJECTIVE

Birth weight is a good predictor of fetal intrauterine growth and long-term health, and several studies have evaluated the relationship between metabolites and birth weight. The aim of this study was to investigate the association of cord blood metabolomics and lipidomics with birth weight, using a two-stage discovery and validation approach.

METHODS

Firstly, a pseudotargeted metabolomics approach was applied to detect metabolites in 504 cord blood samples in the discovery set enrolled from the Wuhan Healthy Baby Cohort, China. Metabolome-wide association scan analysis and pathway enrichment were applied to identify metabolites and metabolic pathways that were significantly associated with birth weight adjusted for gestational age Z-score (BW Z-score). Logistic regression models were used to analyze the association of metabolites in the most significantly associated pathways with small-for-gestational age (SGA) at delivery and low birth weight (LBW). Subsequently, 350 cord blood samples in a validation cohort were subjected to targeted analysis to validate the metabolites identified by screening in the discovery cohort.

RESULTS

In the discovery set, of 2566 metabolites detected, 2418 metabolites were retained for subsequent analysis after data preprocessing. Of these, 513 metabolites were significantly associated with BW Z-score (P-value adjusted for false discovery rate (PFDR) < 0.05), of which 298 Kyoto Encyclopedia of Genes and Genomes (KEGG)-annotated metabolites were included in the pathway analysis. The primary bile acid biosynthesis pathway was the most relevant metabolic pathway associated with BW Z-score. Elevated cord plasma primary bile acids were associated with lower BW Z-score and higher risk of SGA or LBW in the discovery and validation cohorts. In the validation set, a 2-fold increase in taurochenodeoxycholic acid (TCDCA) and in taurocholic acid (TCA) was associated with a decrease in BW Z-score (estimated β coefficient, -0.10 (95% CI, -0.20 to 0.00) and -0.18 (95% CI, -0.31 to -0.04), respectively), after adjusting for covariates. In addition, a 2-fold increase in cord plasma TCDCA and of cord plasma TCA was associated with an increased risk of SGA (adjusted odds ratio (OR), 1.52 (95% CI, 1.00-2.30) and 1.77 (95% CI, 1.05-2.98), respectively). The adjusted OR for LBW, for a 2-fold increase in TCDCA and TCA concentration, were 2.39 (95% CI, 1.00-5.71) and 3.21 (95% CI, 0.96-10.74), respectively.

CONCLUSIONS

These results indicate a significant association of elevated primary bile acids, particularly TCDCA and TCA, in cord blood with lower BW Z-score, as well as increased risk of SGA and LBW. Abnormalities of primary bile acid metabolism may play an important role in restricted fetal development. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

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.

Intrauterine Growth Restriction: Need to Improve Diagnostic Accuracy and Evidence for a Key Role of Oxidative Stress in Neonatal and Long-Term Sequelae

Intrauterine growth restriction (IUGR) and being small for gestational age (SGA) are two distinct conditions with different implications for short- and long-term child development. SGA is present if the estimated fetal or birth weight is below the tenth percentile. IUGR can be identified by additional abnormalities (pathological Doppler sonography, oligohydramnion, lack of growth in the interval, estimated weight below the third percentile) and can also be present in fetuses and neonates with weights above the tenth percentile. There is a need to differentiate between IUGR and SGA whenever possible, as IUGR in particular is associated with greater perinatal morbidity, prematurity and mortality, as well as an increased risk for diseases in later life. Recognizing fetuses and newborns being "at risk" in order to monitor them accordingly and deliver them in good time, as well as to provide adequate follow up care to ameliorate adverse sequelae is still challenging. This review article discusses approaches to differentiate IUGR from SGA and further increase diagnostic accuracy. Since adverse prenatal influences increase but individually optimized further child development decreases the risk of later diseases, we also discuss the need for interdisciplinary follow-up strategies during childhood. Moreover, we present current concepts of pathophysiology, with a focus on oxidative stress and consecutive inflammatory and metabolic changes as key molecular mechanisms of adverse sequelae, and look at future scientific opportunities and challenges. Most importantly, awareness needs to be raised that pre- and postnatal care of IUGR neonates should be regarded as a continuum.

Associations of the placental metabolome with immune maturation up to one year of age in the Swedish NICE-cohort

INTRODUCTION

Allergies and other immune-mediated diseases are thought to result from incomplete maturation of the immune system early in life. We previously showed that infants' metabolites at birth were associated with immune cell subtypes during infancy. The placenta supplies the fetus with nutrients, but may also provide immune maturation signals.

OBJECTIVES

To examine the relationship between metabolites in placental villous tissue and immune maturation during the first year of life and infant and maternal characteristics (gestational length, birth weight, sex, parity, maternal age, and BMI).

METHODS

Untargeted metabolomics was measured using Liquid Chromatography-Mass Spectrometry. Subpopulations of T and B cells were measured using flow cytometry at birth, 48 h, one, four, and 12 months. Random forest analysis was used to link the metabolomics data with the T and B cell sub populations as well as infant and maternal characteristics.

RESULTS

Modest associations (Q2 = 0.2-0.3) were found between the placental metabolome and kappa-deleting recombination excision circles (KREC) at birth and naïve B cells and memory T cells at 12 months. Weak associations were observed between the placental metabolome and sex and parity. Still, most metabolite features of interest were of low intensity compared to associations previously found in cord blood, suggesting that underlying metabolites were not of placental origin.

CONCLUSION

Our results indicate that metabolomic measurements of the placenta may not effectively recognize metabolites important for immune maturation.

Glycolysis: A fork in the path of normal and pathological pregnancy

Glucose metabolism is vital to the survival of living organisms. Since the discovery of the Warburg effect in the 1920s, glycolysis has become a major research area in the field of metabolism. Glycolysis has been extensively studied in the field of cancer and is considered as a promising therapeutic target. However, research on the role of glycolysis in pregnancy is limited. Recent evidence suggests that blastocysts, trophoblasts, decidua, and tumors all acquire metabolic energy at specific stages in a highly similar manner. Glycolysis, carefully controlled throughout pregnancy, maintains a dynamic and coordinated state, so as to maintain the homeostasis of the maternal-fetal interface and ensure normal gestation. In the present review, we investigate metabolic remodeling and the selective propensity of the embryo and placenta for glycolysis. We then address dysregulated glycolysis that occurs in the cellular interactive network at the maternal-fetal interface in miscarriage, preeclampsia, fetal growth restriction, and gestational diabetes mellitus. We provide new insights into the field of maternal-fetal medicine from a metabolic perspective, thus revealing the mystery of human pregnancy.

Identifying placental metabolic biomarkers of preterm birth using nuclear magnetic resonance of intact tissue samples

INTRODUCTION

Our understanding of the etiology of preterm birth (PTB) is incomplete; however, recent evidence has found a strong association between placental dysfunction and PTB. Altered placental metabolism may precede placental dysfunction and therefore the study of placental metabolic profiles could identify early biomarkers of PTB. In this study, we evaluated the placental metabolome in PTB in intact tissue samples using nuclear magnetic resonance (NMR) and spectral editing.

METHODS

Placental tissue samples were collected from nine term pregnancies and nine preterm pregnancies (<37 weeks' gestation). 1H NMR experiments on unprocessed tissue samples were performed using a high field magnet (500 MHz spectrometer) and a comprehensive multiphase NMR probe. The relative concentrations of 23 metabolites were corrected for gestational age and compared between groups.

RESULTS

The relative concentration of valine, glutamate and creatine were significantly decreased while alanine, choline and glucose were elevated in placentas from PTB pregnancies compared to controls (p < 0.05). Multivariate analysis using principal component analysis showed the PTB and control groups were significantly separated (p < 0.0001) and pathway analysis identified perturbations in the glycine, serine and threonine metabolism, aminoacyl-tRNA biosynthesis and valine, leucine and isoleucine biosynthesis pathways.

CONCLUSION

PTB is associated with significant alterations in placental metabolism. This study helps improve our understanding of the etiology of PTB. It also highlights the potential for small molecule metabolites to serve as placental metabolic biomarkers to aid in the prediction and diagnosis of PTB. The results can be translated to clinical use via in utero magnetic resonance spectroscopy.

A Critical Review on the Opportunity to Use Placenta and Innovative Biomonitoring Methods to Characterize the Prenatal Chemical Exposome

Adverse effects associated with chemical exposures during pregnancy include several developmental and reproductive disorders. However, considering the tens of thousands of chemicals present on the market, the effects of chemical mixtures on the developing fetus is still likely underestimated. In this critical review, we discuss the potential to apply innovative biomonitoring methods using high-resolution mass spectrometry (HRMS) on placenta to improve the monitoring of chemical exposure during pregnancy. The physiology of the placenta and its relevance as a matrix for monitoring chemical exposures and their effects on fetal health is first outlined. We then identify several key parameters that require further investigations before placenta can be used for large-scale monitoring in a robust manner. Most critical is the need for standardization of placental sampling. Placenta is a highly heterogeneous organ, and knowledge of the intraplacenta variability of chemical composition is required to ensure unbiased and robust interindividual comparisons. Other important variables include the time of collection, the sex of the fetus, and mode of delivery. Finally, we discuss the first applications of HRMS methods on the placenta to decipher the chemical exposome and describe how the use of placenta can complement biofluids collected on the mother or the fetus.

A screening test proposal for congenital defects based on maternal serum metabolomics profile

BACKGROUND

Historically, noninvasive techniques are only able to identify chromosomal anomalies that accounted for <50% of all congenital defects; the other congenital defects are diagnosed via ultrasound evaluations in the later stages of pregnancy. Metabolomic analysis may provide an important improvement, potentially addressing the need for novel noninvasive and multicomprehensive early prenatal screening tools. A growing body of evidence outlines notable metabolic alterations in different biofluids derived from pregnant women carrying fetuses with malformations, suggesting that such an approach may allow the discovery of biomarkers common to most fetal malformations. In addition, metabolomic investigations are inexpensive, fast, and risk-free and often generate high performance screening tests that may allow early detection of a given pathology.

OBJECTIVE

This study aimed to evaluate the diagnostic accuracy of an ensemble machine learning model based on maternal serum metabolomic signatures for detecting fetal malformations, including both chromosomal anomalies and structural defects.

STUDY DESIGN

This was a multicenter observational retrospective study that included 2 different arms. In the first arm, a total of 654 Italian pregnant women (334 cases with fetuses with malformations and 320 controls with normal developing fetuses) were enrolled and used to train an ensemble machine learning classification model based on serum metabolomics profiles. In the second arm, serum samples obtained from 1935 participants of the New Zealand Screening for Pregnancy Endpoints study were blindly analyzed and used as a validation cohort. Untargeted metabolomics analysis was performed via gas chromatography-mass spectrometry. Of note, 9 individual machine learning classification models were built and optimized via cross-validation (partial least squares-discriminant analysis, linear discriminant analysis, naïve Bayes, decision tree, random forest, k-nearest neighbor, artificial neural network, support vector machine, and logistic regression). An ensemble of the models was developed according to a voting scheme statistically weighted by the cross-validation accuracy and classification confidence of the individual models. This ensemble machine learning system was used to screen the validation cohort.

RESULTS

Significant metabolic differences were detected in women carrying fetuses with malformations, who exhibited lower amounts of palmitic, myristic, and stearic acids; N-α-acetyllysine; glucose; L-acetylcarnitine; fructose; para-cresol; and xylose and higher levels of serine, alanine, urea, progesterone, and valine (P<.05), compared with controls. When applied to the validation cohort, the screening test showed a 99.4%±0.6% accuracy (specificity of 99.9%±0.1% [1892 of 1894 controls correctly identified] with a sensitivity of 78%±6% [32 of 41 fetal malformations correctly identified]).

CONCLUSION

This study provided clinical validation of a metabolomics-based prenatal screening test to detect the presence of congenital defects. Further investigations are needed to enable the identification of the type of malformation and to confirm these findings on even larger study populations.

The Exploration of Fetal Growth Restriction Based on Metabolomics: A Systematic Review

Fetal growth restriction (FGR) is a common complication of pregnancy and a significant cause of neonatal morbidity and mortality. The adverse effects of FGR can last throughout the entire lifespan and increase the risks of various diseases in adulthood. However, the etiology and pathogenesis of FGR remain unclear. This study comprehensively reviewed metabolomics studies related with FGR in pregnancy to identify potential metabolic biomarkers and pathways. Relevant articles were searched through two online databases (PubMed and Web of Science) from January 2000 to July 2022. The reported metabolites were systematically compared. Pathway analysis was conducted through the online MetaboAnalyst 5.0 software. For humans, a total of 10 neonatal and 14 maternal studies were included in this review. Several amino acids, such as alanine, valine, and isoleucine, were high frequency metabolites in both neonatal and maternal studies. Meanwhile, several pathways were suggested to be involved in the development of FGR, such as arginine biosynthesis, arginine, and proline metabolism, glyoxylate and dicarboxylate metabolism, and alanine, aspartate, and glutamate metabolism. In addition, we also included 8 animal model studies, in which three frequently reported metabolites (glutamine, phenylalanine, and proline) were also present in human studies. In general, this study summarized several metabolites and metabolic pathways which may help us to better understand the underlying metabolic mechanisms of FGR.

Fetal growth restriction and stillbirth: Biomarkers for identifying at risk fetuses

Fetal growth restriction (FGR) is a major cause of stillbirth, prematurity and impaired neurodevelopment. Its etiology is multifactorial, but many cases are related to impaired placental development and dysfunction, with reduced nutrient and oxygen supply. The fetus has a remarkable ability to respond to hypoxic challenges and mounts protective adaptations to match growth to reduced nutrient availability. However, with progressive placental dysfunction, chronic hypoxia may progress to a level where fetus can no longer adapt, or there may be superimposed acute hypoxic events. Improving detection and effective monitoring of progression is critical for the management of complicated pregnancies to balance the risk of worsening fetal oxygen deprivation in utero, against the consequences of iatrogenic preterm birth. Current surveillance modalities include frequent fetal Doppler ultrasound, and fetal heart rate monitoring. However, nearly half of FGR cases are not detected in utero, and conventional surveillance does not prevent a high proportion of stillbirths. We review diagnostic challenges and limitations in current screening and monitoring practices and discuss potential ways to better identify FGR, and, critically, to identify the “tipping point” when a chronically hypoxic fetus is at risk of progressive acidosis and stillbirth.

A Metabolomic Profiling of Intra-Uterine Growth Restriction in Placenta and Cord Blood Points to an Impairment of Lipid and Energetic Metabolism

(1) Background: Intrauterine growth restriction (IUGR) involves metabolic changes that may be responsible for an increased risk of metabolic and cardiovascular diseases in adulthood. Several metabolomic profiles have been reported in maternal blood and urine, amniotic fluid, cord blood and newborn urine, but the placenta has been poorly studied so far. (2) Methods: To decipher the origin of this metabolic reprogramming, we conducted a targeted metabolomics study replicated in two cohorts of placenta and one cohort of cord blood by measuring 188 metabolites by mass spectrometry. (3) Results: OPLS-DA multivariate analyses enabled clear discriminations between IUGR and controls, with good predictive capabilities and low overfitting in the two placental cohorts and in cord blood. A signature of 25 discriminating metabolites shared by both placental cohorts was identified. This signature points to sharp impairment of lipid and mitochondrial metabolism with an increased reliance on the creatine-phosphocreatine system by IUGR placentas. Increased placental insulin resistance and significant alteration of fatty acids oxidation, together with relatively higher phospholipase activity in IUGR placentas, were also highlighted. (4) Conclusions: Our results show a deep lipid and energetic remodeling in IUGR placentas that may have a lasting effect on the fetal metabolism.

Placental metabolic profiling in gestational diabetes mellitus: An important role of fatty acids

Aim

Gestational diabetes mellitus (GDM) is the most common metabolic disorder during pregnancy. Accumulating studies have reported metabolites that are significantly associated with the development of GDM. However, studies on the metabolism of placenta, the most important organ of maternal‐fetal energy and material transport, are extremely rare. This study aimed to identify and discuss the relationship between differentially expressed metabolites (DEM) and clinical parameters of the mothers and newborns.

Methods

In this study, metabolites from 63 placenta tissues (32 GDM and 31 normal controls) were assayed by ultra‐performance liquid chromatography‐high resolution mass spectrometry (UPLC‐HRMS).

Results

A total of 1297 annotated metabolites were detected, of which 87 significantly different in GDM placenta. Lipids and lipid‐like molecules accounted for 62.1% of DEM as they were significantly enriched via the “biosynthesis of unsaturated fatty acids” and “fatty acid biosynthesis” pathways. Linoleic acid and α‐linolenic acid appeared to be good biomarkers for the prediction and diagnosis of GDM. In addition, the level of PC(14:0/18:0) was negatively correlated with neonatal weight. 14 metabolites significantly different in male and female offspring, with the most increase in female newborns.

Conclusion

Even if maternal blood glucose level is well controlled, there are still metabolic abnormalities in GDM. Lipids and lipid‐like molecules were the main differential metabolites, especially unsaturated fatty acids.

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.

Metabolic infrastructure of pregnant women with methylenetetrahydrofolate reductase polymorphisms: A metabolomic analysis

The aim of this study was to demonstrate the altered metabolic infrastructure of pregnant women with methylenetetrahydrofolate reductase (MTHFR) polymorphisms at first trimester and during delivery. Eight singleton pregnant women with MTHFR polymorphisms were compared with 10 normal pregnant women. Maternal blood samples were obtained twice during their pregnancy period (between the 11th and 14th gestational weeks and during delivery). Metabolomic analysis was performed using GC-MS. The GC-MS based metabolomic profile helped identify 95 metabolites in the plasma samples. In the MTHFR group, the levels of 1-monohexadecanoylglycerol, pyrophosphate, benzoin, and linoleic acid significantly decreased (P ˂ 0.05 for all), whereas the levels of glyceric acid, l-tryptophan, l-alanine, l-proline, norvaline, l-threonine, and myo-inositol significantly increased (P ˂ 0.01 for the first two metabolites, P ˂ 0.05 for the others) at 11-14 gestational weeks. Conversely, the levels of benzoin, 1-monohexadecanoylglycerol, pyruvic acid, l-proline, phosphoric acid, epsilon-caprolactam, and pipecolic acid significantly decreased in the MTHFR group, whereas metabolites such as hexadecanoic acid and 2-hydroxybutyric acid increased significantly in the study group during delivery. An impaired energy metabolism pathway, vitamin B complex disorders, tendency for metabolic acidosis (oxidative stress), and the need for cell/tissue support seem prevalent in pregnancies with MTHFR polymorphisms.