Detection and identification of novel metabolomic biomarkers in preeclampsia

Plasma metabolic profile reveals signatures of maternal health during gestational hypertension and preeclampsia without and with severe features

Preeclampsia, a pregnancy-specific syndrome, poses substantial risks to maternal and neonatal health, particularly in cases with severe features. Our study focuses on evaluating the impact of low molecular weight metabolites on the intricate mechanisms and pathways involved in the pathophysiology of preeclampsia when severe features are present. We aim to pinpoint the distinct metabolomic profile in maternal plasma during pregnancies affected by hypertensive disorders and to correlate the metabolite levels with the clinical characteristics of the study cohort. A total of 173 plasma samples were collected, comprising 36 healthy pregnant women (HP), 52 patients with gestational hypertension (GH), 43 with preeclampsia without (PE-), and 42 with severe features (PE+). Nuclear magnetic resonance spectroscopy and metabolite identification were conducted to establish the metabolomic profiles. Univariate and chemometric analyses were conducted using MetaboAnalyst, and correlations were performed using GraphPad Prism. Our study unveils distinct metabolomic profiles differentiating HP women, patients featuring GH, and patients with PE-and PE+. Our analysis highlights an increase in acetate, N,N-dimethylglycine, glutamine, alanine, valine, and creatine levels in the PE+ group compared to the HP and GH groups. The PE+ group exhibited higher concentrations of N,N-dimethylglycine, glutamine, alanine, and valine compared to the PE-group. Moreover, elevated levels of specific metabolites, including N,N-dimethylglycine, alanine, and valine, were associated with increased blood pressure, worse obstetric outcomes, and poorer end-organ function, particularly renal and hepatic damage. Metabolomic analysis of PE+ individuals indicates heightened disturbances in nitrogen metabolism, methionine, and urea cycles. Additionally, the exacerbated metabolic disturbance may have disclosed renal impairment and hepatic dysfunction, evidenced by elevated levels of creatine and alanine. These findings not only contribute novel insights but also provide a more comprehensive understanding of the pathophysiological mechanisms at play in cases of PE+.

Coordinated Metabolic Responses Facilitate Cardiac Growth in Pregnancy and Exercise

PURPOSE OF REVIEW

Pregnancy and exercise are systemic stressors that promote physiological growth of the heart in response to repetitive volume overload and maintenance of cardiac output. This type of remodeling is distinct from pathological hypertrophy and involves different metabolic mechanisms that facilitate growth; however, it remains unclear how metabolic changes in the heart facilitate growth and if these processes are similar in both pregnancy- and exercise-induced cardiac growth.

RECENT FINDINGS

The ability of the heart to metabolize a myriad of substrates balances cardiac demands for energy provision and anabolism. During pregnancy, coordination of hormonal status with cardiac reductions in glucose oxidation appears important for physiological growth. During exercise, a reduction in cardiac glucose oxidation also appears important for physiological growth, which could facilitate shuttling of glucose-derived carbons into biosynthetic pathways for growth. Understanding the metabolic underpinnings of physiological cardiac growth could provide insight to optimize cardiovascular health and prevent deleterious remodeling, such as that which occurs from postpartum cardiomyopathy and heart failure. This short review highlights the metabolic mechanisms known to facilitate pregnancy-induced and exercise-induced cardiac growth, both of which require changes in cardiac glucose metabolism for the promotion of growth. In addition, we mention important similarities and differences of physiological cardiac growth in these models as well as discuss current limitations in our understanding of metabolic changes that facilitate growth.

Relationship between the concentration of ergothioneine in plasma and the likelihood of developing pre-eclampsia

Ergothioneine, an antioxidant nutraceutical mainly at present derived from the dietary intake of mushrooms, has been suggested as a preventive for pre-eclampsia (PE). We analysed early pregnancy samples from a cohort of 432 first time mothers as part of the Screening for Endpoints in Pregnancy (SCOPE, European branch) project to determine the concentration of ergothioneine in their plasma. There was a weak association between the ergothioneine levels and maternal age but none for BMI. Of these 432 women, 97 went on to develop pre-term (23) or term (74) PE. If a threshold was set at the 90th percentile of the reference range in the control population (≥462 ng/ml), only one of these 97 women (1%) developed PE, versus 96/397 (24.2%) whose ergothioneine level was below this threshold. One possible interpretation of these findings, consistent with previous experiments in a reduced uterine perfusion model in rats, is that ergothioneine may indeed prove protective against PE in humans. An intervention study of some kind now seems warranted.

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

BACKGROUND

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

OBJECTIVE

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

STUDY DESIGN

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

RESULTS

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

CONCLUSION

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

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.

The Interplay between Pathophysiological Pathways in Early-Onset Severe Preeclampsia Unveiled by Metabolomics

INTRODUCTION

Preeclampsia is a multi-system disorder unique to pregnancy responsible for a great part of maternal and perinatal morbidity and mortality. The precise pathogenesis of this complex disorder is still unrevealed.

METHODS

We examined the pathophysiological pathways involved in early-onset preeclampsia, a specific subgroup representing its most severe presentation, using LC-MS/MS metabolomic analysis based on multi-level extraction of lipids and small metabolites from maternal blood samples, collected at the time of diagnosis from 14 preeclamptic and six matched healthy pregnancies. Statistical analysis comprised multivariate and univariate approaches with the application of over representation analysis to identify differential pathways.

RESULTS

A clear difference between preeclamptic and control pregnancies was observed in principal component analysis. Supervised multivariate analysis using orthogonal partial least square discriminant analysis provided a robust model with goodness of fit (R²X = 0.91, p = 0.002) and predictive ability (Q²Y = 0.72, p < 0.001). Finally, univariate analysis followed by 5% false discovery rate correction indicated 82 metabolites significantly altered, corresponding to six overrepresented pathways: (1) aminoacyl-tRNA biosynthesis; (2) arginine biosynthesis; (3) alanine, aspartate and glutamate metabolism; (4) D-glutamine and D-glutamate metabolism; (5) arginine and proline metabolism; and (6) histidine metabolism.

CONCLUSION

Metabolomic analysis focusing specifically on the early-onset severe form of preeclampsia reveals the interplay between pathophysiological pathways involved in this form. Future studies are required to explore new therapeutic approaches targeting these altered metabolic pathways in early-onset preeclampsia.

Metabolomics Applied to Cord Serum in Preeclampsia Newborns: Implications for Neonatal Outcomes

Preeclampsia (PE) is one of the leading causes of maternal and perinatal morbidity and mortality. However, it is still uncertain how PE affects neonate metabolism. We conducted an untargeted metabolomics analysis of cord blood to explore the metabolic changes in PE neonates. Umbilical cord serum samples from neonates with preeclampsia (n = 29) and non-preeclampsia (non-PE) (n = 32) pregnancies were analyzed using the UHPLC-QE-MS metabolomic platform. Different metabolites were screened, and pathway analysis was conducted. A subgroup analysis was performed among PE neonates to compare the metabolome between appropriate-for-gestational-age infants (n = 21) and small-for-gestational-age (SGA) infants (n = 8). A total of 159 different metabolites were detected in PE and non-PE neonates. Creatinine, N4-acetylcytidine, sphingomyelin (D18:1/16:0), pseudouridine, uric acid, and indolelactic acid were the most significant differential metabolites in the cord serum of PE neonates. Differential metabolite levels were elevated in PE neonates and were involved in the following metabolic pathways: glycine, serine, and threonine metabolism; sphingolipid, glyoxylate, and dicarboxylate metabolism; and arginine biosynthesis. In PE neonates, SGA neonates showed increased levels of hexacosanoyl carnitine and decreased abundance of 3-hydroxybutyric acid and 3-sulfinoalanine. Taurine-related metabolism and ketone body-related pathways were mainly affected. Based on the UHPLC-QE-MS metabolomics analysis, we identified the metabolic profiles of PE and SGA neonates. The abundance of metabolites related to certain amino acid, sphingolipid, and energy metabolism increased in the umbilical cord serum of PE neonates.

Significance of analysis of lipid extracts in cervical canal secretion for diagnosing of placenta-associated complications of pregnancy

Omics technologies hold great potential as the basis for development of the new diagnostic approaches in obstetrics. Cervicovaginal fluid (CVF) as part of the mother-placenta-fetus system can be used to diagnose obstetric complications. This study aimed to identify the features of lipid composition of the cervical canal secretion peculiar to Intrauterine Growth Restriction (IUGR) and preeclampsia (PE). We took CVF samples from 57 pregnant women and subjected them to an in-depth clinical-anamnestic and mass-spectrometric analysis. Lipid extracts of CVF were analyzed with a liquid chromatography system coupled with a mass analyzer. As a result, we identified 239 lipid compounds. In case of 17 lipids, mathematical analysis revealed significant differences between samples from women with normal pregnancy indicator values (normal group) and patients from the IUGR group (p < 0.05). As for the normal group and PE group patients, there were significant differences identified for 3 lipids (p < 0.05). Comparison of samples from the PE and IUGR groups yielded statistically significant differences in levels of two lipids (p < 0.05). Mainly, the lipids were oxylipins, sphingomyelins, triglycerides, and cardiolipins. The developed diagnostic model had the sensitivity of 0.81 and specificity of 0.91 (cut-off level — 0.50; AUC — 0.85). The data obtained are valuable in the context of development of the new methods of diagnosing placentaassociated complications of pregnancy and for understanding new mechanisms of pathogenesis of these complications.

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.

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.

Metabolomic biomarkers in midtrimester maternal plasma can accurately predict the development of preeclampsia

Early identification of patients at risk of developing preeclampsia (PE) would allow providers to tailor their prenatal management and adopt preventive strategies, such as low-dose aspirin. Nevertheless, no mid-trimester biomarkers have as yet been proven useful for prediction of PE. This study investigates the ability of metabolomic biomarkers in mid-trimester maternal plasma to predict PE. A case–control study was conducted including 33 pregnant women with mid-trimester maternal plasma (gestational age [GA], 16–24 weeks) who subsequently developed PE and 66 GA-matched controls with normal outcomes (mid-trimester cohort). Plasma samples were comprehensively profiled for primary metabolic and lipidomic signatures based on gas chromatography time-of-flight mass spectrometry (GC-TOF MS) and liquid chromatography Orbitrap mass spectrometry (LC-Orbitrap MS). A potential biomarker panel was computed based on binary logistic regression and evaluated using receiver operating characteristic (ROC) analysis. To evaluate whether this panel can be also used in late pregnancy, a retrospective cohort study was conducted using plasma collected from women who delivered in the late preterm period because of PE (n = 13) or other causes (n = 21) (at-delivery cohort). Metabolomic biomarkers were compared according to the indication for delivery. Performance of the metabolomic panel to identify patients with PE was compared also to a commonly used standard, the plasma soluble fms-like tyrosine kinase-1/placental growth factor (sFlt-1/PlGF) ratio. In the mid-trimester cohort, a total of 329 metabolites were identified and semi-quantified in maternal plasma using GC-TOF MS and LC-Orbitrap-MS. Binary logistic regression analysis proposed a mid-trimester biomarker panel for the prediction of PE with five metabolites (SM C28:1, SM C30:1, LysoPC C19:0, LysoPE C20:0, propane-1,3-diol). This metabolomic model predicted PE better than PlGF (AUC [95% CI]: 0.868 [0.844–0.891] vs 0.604 [0.485–0.723]) and sFlt-1/PlGF ratio. Analysis of plasma from the at-delivery cohort confirmed the ability of this biomarker panel to distinguish PE from non-PE, with comparable discrimination power to that of the sFlt-1/PlGF ratio. In conclusion, an integrative metabolomic biomarker panel in mid-trimester maternal plasma can accurately predict the development of PE and showed good discriminatory power in patients with PE at delivery.

A Europium-based MOF Fluorescent Probe for Efficiently Detecting Malachite Green and Uric Acid

Lanthanide (such as Tb and Eu) metal-organic frameworks (MOFs) have been widely used in fluorescent probes because of their multiple coordination modes and brilliant fluorescence characteristic. Many lanthanide MOFs were applied in detecting metal ions, inorganic anions, and small molecules. However, it's rarely reported that Ln-MOF was devoted to detecting malachite green (MG) and uric acid (UA). We prepared a europium-based metal-organic framework (Eu-TDA) (TDA = 2,5-thiophenedicarboxylic acid group). Luminescence studies demonstrated that Eu-TDA can rapidly detect MG and UA with excellent selectivity and sensitivity, where individual quenching efficiency K_sv (MG: 5.8 × 10⁵ M^-1; UA: 4.15 × 10⁴ M^-1) and detection limit (MG: 0.0221 μM; UA: 0.689 μM) were regarded as the excellent MOF sensors for detecting MG and UA. The quenching of Eu-TDA's fluorescence emission by MG and UA was likely due to the spectral overlap, energy transfer, and competition. Among 11 metal cations and 14 anions, Eu-TDA can quickly and effectively recognize MG and UA with highly selective and sensitive properties. Our method possesses potential application in detecting UA in human blood and MG in the fishpond.

Untargeted analysis of plasma samples from pre-eclamptic women reveals polar and apolar changes in the metabolome

INTRODUCTION

Pre-eclampsia is a hypertensive gestational disorder that affects approximately 5% of all pregnancies.

OBJECTIVES

As the pathophysiological processes of pre-eclampsia are still uncertain, the present case-control study explored underlying metabolic processes characterising this disease.

METHODS

Maternal peripheral plasma samples were collected from pre-eclamptic (n = 32) and healthy pregnant women (n = 35) in the third trimester. After extraction, high-resolution mass spectrometry-based untargeted metabolomics was used to profile polar and apolar metabolites and the resulting data were analysed via uni- and multivariate statistical approaches.

RESULTS

The study demonstrated that the metabolome undergoes substantial changes in pre-eclamptic women. Amongst the most discriminative metabolites were hydroxyhexacosanoic acid, diacylglycerols, glycerophosphoinositols, nicotinamide adenine dinucleotide metabolites, bile acids and products of amino acid metabolism.

CONCLUSIONS

The putatively identified compounds provide sources for novel hypotheses to help understanding of the underlying biochemical pathology of pre-eclampsia.

The plasma metabolome of women in early pregnancy differs from that of non-pregnant women

BACKGROUND

In comparison to the non-pregnant state, the first trimester of pregnancy is characterized by systemic adaptation of the mother. The extent to which these adaptive processes are reflected in the maternal blood metabolome is not well characterized.

OBJECTIVE

To determine the differences between the plasma metabolome of non-pregnant and pregnant women before 16 weeks gestation.

STUDY DESIGN

This study included plasma samples from 21 non-pregnant women and 50 women with a normal pregnancy (8-16 weeks of gestation). Combined measurements by ultrahigh performance liquid chromatography/tandem mass spectrometry and by gas chromatography/mass spectrometry generated molecular abundance measurements for each sample. Molecular species detected in at least 10 samples were included in the analysis. Differential abundance was inferred based on false discovery adjusted p-values (FDR) from Mann-Whitney-Wilcoxon U tests <0.1 and a minimum median abundance ratio (fold change) of 1.5. Alternatively, metabolic data were quantile normalized to remove sample-to-sample differences in the overall metabolite abundance (adjusted analysis).

RESULTS

Overall, 637 small molecules met the inclusion criteria and were tested for association with pregnancy; 44% (281/637) of small molecules had significantly different abundance, of which 81% (229/281) were less abundant in pregnant than in non-pregnant women. Eight percent (14/169) of the metabolites that remained significant in the adjusted analysis also changed as a function of gestational age. A pathway analysis revealed enrichment in steroid metabolites related to sex hormones, caffeine metabolites, lysolipids, dipeptides, and polypeptide bradykinin derivatives (all, FDR < 0.1).

CONCLUSIONS

This high-throughput mass spectrometry study identified: 1) differences between pregnant vs. non-pregnant women in the abundance of 44% of the profiled plasma metabolites, including known and novel molecules and pathways; and 2) specific metabolites that changed with gestational age.

Metabolomics applied to maternal and perinatal health: a review of new frontiers with a translation potential

The prediction or early diagnosis of maternal complications is challenging mostly because the main conditions, such as preeclampsia, preterm birth, fetal growth restriction, and gestational diabetes mellitus, are complex syndromes with multiple underlying mechanisms related to their occurrence. Limited advances in maternal and perinatal health in recent decades with respect to preventing these disorders have led to new approaches, and "omics" sciences have emerged as a potential field to be explored. Metabolomics is the study of a set of metabolites in a given sample and can represent the metabolic functioning of a cell, tissue or organism. Metabolomics has some advantages over genomics, transcriptomics, and proteomics, as metabolites are the final result of the interactions of genes, RNAs and proteins. Considering the recent "boom" in metabolomic studies and their importance in the research agenda, we here review the topic, explaining the rationale and theory of the metabolomic approach in different areas of maternal and perinatal health research for clinical practitioners. We also demonstrate the main exploratory studies of these maternal complications, commenting on their promising findings. The potential translational application of metabolomic studies, especially for the identification of predictive biomarkers, is supported by the current findings, although they require external validation in larger datasets and with alternative methodologies.

Metabolomics of Pregnancy Complications: Emerging Application of Maternal Hair

In recent years, the study of metabolomics has begun to receive increasing international attention, especially as it pertains to medical research. This is due in part to the potential for discovery of new biomarkers in the metabolome and to a new understanding of the "exposome", which refers to the endogenous and exogenous compounds that reflect external exposures. Consequently, metabolomics research into pregnancy-related issues has increased. Biomarkers discovered through metabolomics may shed some light on the etiology of certain pregnancy-related complications and their adverse effects on future maternal health and infant development and improve current clinical management. The discoveries and methods used in these studies will be compiled and summarized within the following paper. A further focus of this paper is the use of hair as a biological sample, which is gaining increasing attention across diverse fields due to its noninvasive sampling method and the metabolome stability. Its significance in exposome studies will be considered in this review, as well as the potential to associate exposures with adverse pregnancy outcomes. Currently, hair has been used in only two metabolomics studies relating to fetal growth restriction (FGR) and gestational diabetes mellitus (GDM).

Metabolic Biomarkers of Monochorionic Twins Complicated With Selective Intrauterine Growth Restriction in Cord Plasma and Placental Tissue

The selective intrauterine growth restriction (sIUGR) of monochorionic diamniotic (MCDC) twins causes phenotypic growth discordance, which is correlated with metabolomic pertubations. A global, untargeted identification of the metabolic fingerprint may help elucidate the etiology of sIUGR. Umbilical cord blood and placentas collected from 15 pairs of sIUGR monochorionic twins, 24 pairs of uncomplicated twins, and 14 singletons diagnosed with intrauterine growth restriction (IUGR) were subjected to gas chromatography-mass spectrometry based metabolomic analyses. Supervised multivariate regression analysis and pathway analysis were performed to compare control twins with sIUGR twins. A generalized estimating equation (GEE) model was utilized to explore metabolic differences within sIUGR co-twins. Linear logistic regression was applied to screen metabolites that significantly differed in concentration between control twins and sIUGR twins or IUGR singletons. Umbilical cord blood demonstrated better global metabolomic separation of sIUGR and control twins compared to the placenta. Disrupted amino acid and fatty acid metabolism as well as high levels of exposure to environmental xenobiotics were associated with sIUGR. The metabolic abnormalities in MCDA twins suggested that in utero growth discordance is caused by intrauterine and extrauterine environmental factors, rather than genetics. Thus, this study provides new therapeutic targets and strategies for sIUGR management and prevention.

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.

Cerebral Osmolytes and Plasma Osmolality in Pregnancy and Preeclampsia: A Proton Magnetic Resonance Spectroscopy Study

BACKGROUND

Cerebral complications contribute substantially to mortality in preeclampsia. Pregnancy calls for extensive maternal adaptations, some associated with increased propensity for seizures, but the pathophysiology behind the eclamptic seizures is not fully understood. Plasma osmolality and sodium levels are lowered in pregnancy. This could result in extrusion of cerebral organic osmolytes, including the excitatory neurotransmitter glutamate, but this remains to be determined. The hypothesis of this study was that cerebral levels of organic osmolytes are decreased during pregnancy, and that this decrease is even more pronounced in women with preeclampsia.

METHODS

We used proton magnetic resonance spectroscopy to compare levels of cerebral organic osmolytes, in women with preeclampsia (n = 30), normal pregnancy (n = 32), and nonpregnant controls (n = 16). Cerebral levels of organic osmolytes were further correlated to plasma osmolality and plasma levels of glutamate and sodium.

RESULTS

Compared to nonpregnant women, women with normal pregnancy and preeclampsia had lower levels of the cerebral osmolytes, myo-inositol, choline and creatine (P = 0.001 or less), and all these metabolites correlated with each other (P < 0.05). Women with normal pregnancies and preeclampsia had similar levels of osmolytes, except for glutamate, which was significantly lower in preeclampsia. Cerebral and plasma glutamate levels were negatively correlated with each other (P < 0.008), and myo-inositol, choline and creatine levels were all positively correlated with both plasma osmolality and sodium levels (P < 0.05).

CONCLUSIONS

Our results indicate that pregnancy is associated with extrusion of cerebral organic osmolytes. This includes the excitatory neurotransmitter glutamate, which may be involved in the pathophysiology of seizures in preeclampsia.

Utility of metabolic profiling of serum in the diagnosis of pregnancy complications

INTRODUCTION

Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states.

METHODS

We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies.

RESULTS

Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets).

CONCLUSIONS

A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies.

Andrée Gruslin award lecture: Metabolomics as an important modality to better understand preeclampsia

Preeclampsia (PE) is a complex disorder that affects 3-5% of all pregnancies and is a leading cause of maternal and fetal morbidity and mortality. To date, the heterogeneity of clinical presentation, disease severity and outcomes have limited significant advances in early prediction, diagnosis, and therapeutic intervention of PE. The rapidly expanding field of metabolomics, which has the capacity to quantitatively detect low molecular weight compounds (metabolites) in tissue and biological fluids, shows tremendous promise in gaining a better understanding of PE. This review will discuss this emerging field and its contribution to recent advances in the understanding of PE pathophysiology, and identification of early predictive metabolic biomarkers for this complex disorder.

Applications of Metabolomics in the Study and Management of Preeclampsia; A Review of the Literature

Introduction

Preeclampsia represents a major public health burden worldwide, but predictive and diagnostic biomarkers are lacking. Metabolomics is emerging as a valuable approach to generating novel biomarkers whilst increasing the mechanistic understanding of this complex condition.

Objectives

To summarize the published literature on the use of metabolomics as a tool to study preeclampsia.

Methods

PubMed and Web of Science were searched for articles that performed metabolomic profiling of human biosamples using either Mass-spectrometry or Nuclear Magnetic Resonance based approaches and which included preeclampsia as a primary endpoint.

Results

Twenty-eight studies investigating the metabolome of preeclampsia in a variety of biospecimens were identified. Individual metabolite and metabolite profiles were reported to have discriminatory ability to distinguish preeclamptic from normal pregnancies, both prior to and post diagnosis. Lipids and carnitines were among the most commonly reported metabolites. Further work and validation studies are required to demonstrate the utility of such metabolites as preeclampsia biomarkers.

Conclusion

Metabolomic-based biomarkers of preeclampsia have yet to be integrated into routine clinical practice. However, metabolomic profiling is becoming increasingly popular in the study of preeclampsia and is likely to be a valuable tool to better understand the pathophysiology of this disorder and to better classify its subtypes, particularly when integrated with other omic data.

Absolute Quantification of Uric Acid in Human Urine Using Surface Enhanced Raman Scattering with the Standard Addition Method

High levels of uric acid in urine and serum can be indicative of hypertension and the pregnancy related condition, preeclampsia. We have developed a simple, cost-effective, portable surface enhanced Raman scattering (SERS) approach for the routine analysis of uric acid at clinically relevant levels in urine patient samples. This approach, combined with the standard addition method (SAM), allows for the absolute quantification of uric acid directly in a complex matrix such as that from human urine. Results are highly comparable and in very good agreement with HPLC results, with an average <9% difference in predictions between the two analytical approaches across all samples analyzed, with SERS demonstrating a 60-fold reduction in acquisition time compared with HPLC. For the first time, clinical prepreeclampsia patient samples have been used for quantitative uric acid detection using a simple, rapid colloidal SERS approach without the need for complex data analysis.

Integration of metabolomic and transcriptomic networks in pregnant women reveals biological pathways and predictive signatures associated with preeclampsia

INTRODUCTION

Preeclampsia is a leading cause of maternal and fetal mortality worldwide, yet its exact pathogenesis remains elusive.

OBJECTIVES

This study, nested within the Vitamin D Antenatal Asthma Reduction Trial (VDAART), aimed to develop integrated omics models of preeclampsia that have utility in both prediction and in the elucidation of underlying biological mechanisms.

METHODS

Metabolomic profiling was performed on first trimester plasma samples of 47 pregnant women from VDAART who subsequently developed preeclampsia and 62 controls with healthy pregnancies, using liquid-chromatography tandem mass-spectrometry. Metabolomic profiles were generated based on logistic regression models and assessed using Received Operator Characteristic Curve analysis. These profiles were compared to profiles from generated using third trimester samples. The first trimester metabolite profile was then integrated with a pre-existing transcriptomic profile using network methods.

RESULTS

In total, 72 (0.9%) metabolite features were associated (p<0.01) with preeclampsia after adjustment for maternal age, race, and gestational age. These features had moderate to good discriminatory ability; in ROC curve analyses a summary score based on these features displayed an area under the curve (AUC) of 0.794 (95%CI 0.700, 0.888). This profile retained the ability to distinguish preeclamptic from healthy pregnancies in the third trimester (AUC:0.762 (95% CI 0.663, 0.860)). Additionally, metabolite set enrichment analysis identified common pathways, including glycerophospholipid metabolism, at the two time-points. Integration with the transcriptomic signature refined these results suggesting a particular role for lipid imbalance, immune function and the circulatory system.

CONCLUSIONS

These findings suggest it is possible to develop a predictive metabolomic profile of preeclampsia. This profile is characterized by changes in lipid and amino acid metabolism and dysregulation of immune response and can be refined through interaction with transcriptomic data. However validation in larger and more diverse populations is required.

A Dormant Microbial Component in the Development of Preeclampsia

Preeclampsia (PE) is a complex, multisystem disorder that remains a leading cause of morbidity and mortality in pregnancy. Four main classes of dysregulation accompany PE and are widely considered to contribute to its severity. These are abnormal trophoblast invasion of the placenta, anti-angiogenic responses, oxidative stress, and inflammation. What is lacking, however, is an explanation of how these themselves are caused. We here develop the unifying idea, and the considerable evidence for it, that the originating cause of PE (and of the four classes of dysregulation) is, in fact, microbial infection, that most such microbes are dormant and hence resist detection by conventional (replication-dependent) microbiology, and that by occasional resuscitation and growth it is they that are responsible for all the observable sequelae, including the continuing, chronic inflammation. In particular, bacterial products such as lipopolysaccharide (LPS), also known as endotoxin, are well known as highly inflammagenic and stimulate an innate (and possibly trained) immune response that exacerbates the inflammation further. The known need of microbes for free iron can explain the iron dysregulation that accompanies PE. We describe the main routes of infection (gut, oral, and urinary tract infection) and the regularly observed presence of microbes in placental and other tissues in PE. Every known proteomic biomarker of "preeclampsia" that we assessed has, in fact, also been shown to be raised in response to infection. An infectious component to PE fulfills the Bradford Hill criteria for ascribing a disease to an environmental cause and suggests a number of treatments, some of which have, in fact, been shown to be successful. PE was classically referred to as endotoxemia or toxemia of pregnancy, and it is ironic that it seems that LPS and other microbial endotoxins really are involved. Overall, the recognition of an infectious component in the etiology of PE mirrors that for ulcers and other diseases that were previously considered to lack one.

Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes

This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.

Metabolomics and the great obstetrical syndromes--GDM, PET, and IUGR

Gestational diabetes mellitus, intrauterine growth restriction, and preeclamptic toxemia are common pregnancy complications that can have detrimental effects on morbidity and mortality of the mother and fetus as well as long-term health outcomes. Although they are distinct conditions, they may occur together and are often considered together as they share a common etiology of inadequate placental perfusion. The discovery and study of preventative treatments is hampered by a lack of effective screening tools to accurately identify women at the highest risk of disease. Metabolomics, an omic science, is the global quantitative assessment of endogenous metabolites within a biological system. It has proven to be a rapid approach in the identification of biomarkers predictive of the outcome of a pathological condition and the individual's response to a pharmacological treatment. We review the current and potential applications of metabolomics in maternal-fetal medicine, focusing on its use as a biomarker for great obstetrical syndromes diagnosis.

Early predictors of gestational hypertension in a low-risk cohort. Results of a pilot study

OBJECTIVE

To determine if the clinical or biochemical markers used in pregnancy can be applied as early predictors of gestational hypertension.

DESIGN

Prospective cohort study.

POPULATION

315 pregnant women referred from the Prenatal Diagnosis Unit between weeks 10-13 of pregnancy and followed up to the childbirth.

METHODS

Biomarkers were measured in serum specimens in the first and second trimester of pregnancy. Blood pressure (BP) was measured in the first, second and third trimester.

RESULTS

The cumulative incidence of gestational hypertension was 6.01%. In the first trimester gestational hypertension predictors were uric acid greater than 3.15 mg/dl (P=0.01), BMI greater than 24 kg/m (P=0.003) SBP at least 120 mmHg (P=0.02) and DBP at least 71 mmHg (P=0.007). After applied multivariate analysis just uric acid and SBP were statistically significant.

CONCLUSION

In our cohort of healthy pregnant women uric acid above 3.15 mg/dl and SBP at least 120 mmHg are consistent predictors of gestational hypertension in the first trimester. The most important implication of our study is the possibility to identify in the first trimester women at risk to develop gestational hypertension using available markers.

Potential input from metabolomics for exploring and understanding the links between environment and health

Humans may be exposed via their environment to multiple chemicals as a consequence of human activities and use of synthetic products. Little knowledge is routinely generated on the hazards of these chemical mixtures. The metabolomic approach is widely used to identify metabolic pathways modified by diseases, drugs, or exposures to toxicants. This review, based on the state of the art of the current applications of metabolomics in environmental health, attempts to determine whether metabolomics might constitute an original approach to the study of associations between multiple, low-dose environmental exposures in humans. Studying the biochemical consequences of complex environmental exposures is a challenge demanding the development of careful experimental and epidemiological designs, in order to take into account possible confounders associated with the high level of interindividual variability induced by different lifestyles. The choices of populations studied, sampling and storage procedures, statistical tools used, and system biology need to be considered. Suggestions for improved experimental and epidemiological designs are described. Evidence indicates that metabolomics may be a powerful tool in environmental health in the identification of both complex exposure biomarkers directly in human populations and modified metabolic pathways, in an attempt to improve understanding the underlying environmental causes of diseases. Nevertheless, the validity of biomarkers and relevancy of animal-to-human extrapolation remain key challenges that need to be properly explored.

The influence of maternal disease on metabolites measured as part of newborn screening

OBJECTIVE

Measurements of neonatal metabolites are commonly used in newborn screening (NBS) programs to detect inborn errors of metabolism. Variation in these metabolites, particularly in infants born preterm (<37 weeks gestation), can result from multiple etiologies. We sought to evaluate the impact of maternal complications of pregnancy and environmental stressors on NBS metabolites.

METHODS

We examined 49 metabolic biomarkers obtained from routine NBS in 452 infants born preterm for association with maternal environmental stressors and complications of pregnancy.

RESULTS

Neonatal free carnitine (C0, p = 1.4 × 10(-7)), acetylcarnitine (C2, p = 2.7 × 10(-7)), octenoylcarnitine (C8:1, p = 5.2 × 10(-11)) and linoleoylcarnitine (C18:2, p = 9.1 × 10(-7)) were elevated in infants born to preeclamptic mothers. Similar elevations were observed in small for gestational age infants and in infants where labor was not initiated prior to delivery. When accounting for all three factors, associations remained strongest between acylcarnitines and preeclampsia.

CONCLUSION

We observed that maternal conditions, particularly preeclampsia, influence NBS biomarkers. This is important for identifying maternal conditions that influence metabolites measured during routine NBS that are also markers of fetal growth and overall health.

Maternal and cord blood LC-HRMS metabolomics reveal alterations in energy and polyamine metabolism, and oxidative stress in very-low birth weight infants

To assess the global effect of preterm birth on fetal metabolism and maternal-fetal nutrient transfer, we used a mass spectrometric-based chemical phenotyping approach on cord blood obtained at the time of birth. We sampled umbilical venous, umbilical arterial, and maternal blood from mothers delivering very-low birth weight (VLBW, with a median gestational age and weight of 29 weeks, and 1210 g, respectively) premature or full-term (FT) neonates. In VLBW group, we observed a significant elevation in the levels and maternal-fetal gradients of butyryl-, isovaleryl-, hexanoyl- and octanoyl-carnitines, suggesting enhanced short- and medium chain fatty acid β-oxidation in human preterm feto-placental unit. The significant decrease in glutamine-glutamate in preterm arterial cord blood beside lower levels of amino acid precursors of Krebs cycle suggest increased glutamine utilization in the fast growing tissues of preterm fetus with a deregulation in placental glutamate-glutamine shuttling. Enhanced glutathione utilization is likely to account for the decrease in precursor amino acids (serine, betaine, glutamate and methionine) in arterial cord blood. An increase in both the circulating levels and maternal-fetal gradients of several polyamines in their acetylated form (diacetylspermine and acetylputrescine) suggests an enhanced polyamine metabolic cycling in extreme prematurity. Our metabolomics study allowed the identification of alterations in fetal energy, antioxidant defense, and polyamines and purines flux as a signature of premature birth.

First-trimester metabolomic detection of late-onset preeclampsia

OBJECTIVE

We sought to identify first-trimester maternal serum biomarkers for the prediction of late-onset preeclampsia (PE) using metabolomic analysis.

STUDY DESIGN

In a case-control study, nuclear magnetic resonance-based metabolomic analysis was performed on first-trimester maternal serum between 11(+0)-13(+6) weeks of gestation. There were 30 cases of late-onset PE, i.e., requiring delivery ≥37 weeks, and 59 unaffected controls. The concentrations of 40 metabolites were compared between the 2 groups. We also compared 30 early-onset cases to the late-onset group.

RESULTS

A total of 14 metabolites were significantly elevated and 3 significantly reduced in first-trimester serum of late-onset PE patients. A complex model consisting of multiple metabolites and maternal demographic characteristics had a 76.6% sensitivity at 100% specificity for PE detection. A simplified model using fewer predictors yielded 60% sensitivity at 96.6% specificity. Strong separation of late- vs early-onset PE groups was achieved.

CONCLUSION

Significant differences in the first-trimester metabolites were noted in women who went on to developed late-onset PE and between early- and late-onset PE.

Metabolic changes in urine during and after pregnancy in a large, multiethnic population-based cohort study of gestational diabetes

This study aims to identify novel markers for gestational diabetes (GDM) in the biochemical profile of maternal urine using NMR metabolomics. It also catalogs the general effects of pregnancy and delivery on the urine profile. Urine samples were collected at three time points (visit V1: gestational week 8-20; V2: week 28±2; V3 10-16 weeks post partum) from participants in the STORK Groruddalen program, a prospective, multiethnic cohort study of 823 healthy, pregnant women in Oslo, Norway, and analyzed using (1)H-NMR spectroscopy. Metabolites were identified and quantified where possible. PCA, PLS-DA and univariate statistics were applied and found substantial differences between the time points, dominated by a steady increase of urinary lactose concentrations, and an increase during pregnancy and subsequent dramatic reduction of several unidentified NMR signals between 0.5 and 1.1 ppm. Multivariate methods could not reliably identify GDM cases based on the WHO or graded criteria based on IADPSG definitions, indicating that the pattern of urinary metabolites above micromolar concentrations is not influenced strongly and consistently enough by the disease. However, univariate analysis suggests elevated mean citrate concentrations with increasing hyperglycemia. Multivariate classification with respect to ethnic background produced weak but statistically significant models. These results suggest that although NMR-based metabolomics can monitor changes in the urinary excretion profile of pregnant women, it may not be a prudent choice for the study of GDM.

Amino acid profile of plasma and cerebrospinal fluid in preeclampsia

OBJECTIVES

To determine patterns in amino acids (arginine, GABA, glutamate and glutamine) and the diamine (agmatine) in plasma and cerebrospinal fluid (CSF) of mild and severe preeclampsia compared to control patients, using capillary zone electrophoresis to generate methods for refining diagnosis and prognosis and shed light on the pathophysiological mechanisms of preeclampsia.

STUDY DESIGN

This is an observational case-control study in pregnant women that attended the emergency ward of the University Hospital, Mérida, Venezuela, during the period April, 2009-April 2010.

MAIN OUTCOME MEASURES

Molar concentration of amino acids and diamine in plasma and CSF in control, mild and severe preeclampsia patients.

RESULTS

An increase in glutamate plasma levels was observed in mild preeclampsia and even higher in severe patients, while a biphasic response occurred in the CSF samples with a significant increment in mild preeclampsia patients and a decrease in severe preeclampsia patients. GABA significantly decreased both in plasma and CSF in mild preeclampsia with a tendency to return to normal levels in severe preeclampsia patients. Arginine CSF and plasma levels decreased in mild preeclampsia patients and even more in severe preeclampsia while agmatine significantly increased in plasma levels with no changes in CSF.

CONCLUSIONS

The results are discussed in terms of molecules that could be used as biomarkers of the severity of the disease and the possible involvement of these substances in the pathophysiology of preeclampsia.

A metabolomic approach identifies differences in maternal serum in third trimester pregnancies that end in poor perinatal outcome

Metabolomics offers a powerful holistic approach to examine the metabolite composition of biofluids to identify disruptions present in disease. We used ultra performance liquid chromatography-mass spectroscopy on the maternal serum obtained in the third trimester to address the hypothesis that pregnancies ending in poor outcomes (small for gestational age infant, preterm birth, or neonatal intensive care admission, n = 40) would have a different maternal serum metabolic profiles to matched healthy pregnancies (n = 40). Ninety-eight identified metabolic features differed between normal and poor pregnancy outcomes. Classes of metabolites perturbed included free fatty acids, glycerolipids, progesterone metabolites, sterol lipids, vitamin D metabolites, and sphingolipids; these highlight potential molecular mechanisms associated with pregnancy complications in the third trimester linked by placental dysfunction. In this clinical setting, metabolomics has the potential to describe differences in fetoplacental and maternal metabolites in pregnancies with poor pregnancy outcomes compared with controls.

UPLC-MS metabolic profiling of second trimester amniotic fluid and maternal urine and comparison with NMR spectral profiling for the identification of pregnancy disorder biomarkers

We report on the first untargeted UPLC-MS study of 2nd trimester maternal urine and amniotic fluid (AF), to investigate the possible metabolic effects of fetal malformations (FM), gestational diabetes mellitus (GDM) and preterm delivery (PTD). For fetal malformations, considerable metabolite variations were identified in AF and, to a lesser extent, in urine. Using validated PLS-DA models and statistical correlations between UPLC-MS data and previously acquired NMR data, a metabolic picture of fetal hypoxia, enhanced gluconeogenesis, TCA activity and hindered kidney development affecting FM pregnancies was reinforced. Moreover, changes in carnitine, pyroglutamate and polyols were newly noted, respectively, reflecting lipid oxidation, altered placental amino acid transfer and alterations in polyol pathways. Higher excretion of conjugated products in maternal urine was seen suggesting alterations in conjugation reactions. For the pre-diagnostic GDM group, no significant changes were observed, either considering amniotic fluid or maternal urine, whereas, for the pre-PTD group, some newly observed changes were noted, namely, the decrease of particular amino acids and the increase of an hexose (possibly glucose), suggesting alteration in placental amino acid fluxes and a possible tendency for hyperglycemia. This work shows the potential of UPLC-MS for the study of fetal and maternal biofluids, particularly when used in tandem with comparable NMR data. The important roles played by sampling characteristics (e.g. group dimensions) and the specific experimental conditions chosen for MS methods are discussed.

Role of Ureaplasma urealyticum in altering the endothelial metal concentration during preeclampsia

OBJECTIVES

Preeclampsia is a pregnancy specific disorder connected with endothelial cell dysfunction. In vitro stimulation of preeclamptic placental endothelial cell with Ureaplasma urealyticum will help in understanding its relationship with the host cell. Metals and metal-containing compounds are known to play important roles in many biological processes, including metabolic pathway, inflammation and function of proteins.

STUDY DESIGN

The variation in expression of various metals was assessed for the first time using FESEM (Field Emission Scanning Electron Microscope) with EDX (Energy Dispersive X-ray spectroscopy) technique in endothelial cells isolated from normotensive and preeclamptic placenta with and without in vitro U. urealyticum stimulation. The results were correlated with the expression of HSP (heat shock protein) 70 in all the 4 endothelial cells.

RESULTS

Preeclampsia and U. urealyticum infection alters endothelial cell size, HSP70 expression and metal (sodium, potassium, calcium, iron) concentration. There is a significant increase in the concentration of iron and calcium and decrease in HSP70 expression and endothelial cell size in preeclamptic endothelial cell with U. urealyticum stimulation.

CONCLUSION

This work is the first step in the identification of metals pertinent to mollicute infection and lays the foundation for future studies concentrating on characterization of these metal associated or containing molecules. The ionic imbalance observed infers that calcium and iron supplementation should be executed with caution both during preeclampsia and U. urealyticum infection in pregnancy. This study also suggests that the HSP70 mediated protection exhibited in endothelial cell during preeclampsia is lost upon U. urealyticum infection which further contributes to the observed endothelial cell damage.

Decreased mitochondrial fatty acid oxidation in placentas from women with preeclampsia

Preeclampsia is a leading cause of maternal and fetal morbidity and mortality in high and low-income countries. The aetiology of preeclampsia is multifactorial and remains obscure. Some evidences suggest that altered placental fatty acid oxidation might play a role in the pathogenesis of preeclampsia. To reveal if placental fatty acid oxidation is reduced in preeclampsia, we evaluate the expression levels of enzymes of mitochondrial fatty acid oxidation using quantitative Real-time PCR and the fatty acid oxidation rate in placental explants. We found that long-chain 3-hydroxyacyl-CoA dehydrogenase levels and fatty acid oxidation capacity were significantly reduced in placentas from women with preeclampsia.

First-trimester prediction of preeclampsia using metabolomic biomarkers: a discovery phase study

OBJECTIVE

We tested the hypothesis that first-trimester metabolic biomarkers offered a unique profile in women with preeclampsia (PE) in the second half of pregnancy, compared with controls.

METHOD

We conducted a nested case-control study within a prospective cohort of pregnant women followed from the first-trimester to delivery. Cases were those who developed PE at any gestational age, and these were compared with a control group without adverse pregnancy outcome, matched for gestational age within 3 days. We analyzed maternal blood obtained at 11-14 weeks' gestation for 40 acylcarnitine species (C2-C18 saturated, unsaturated, and hydroxylated) and 32 amino acids by liquid chromatography tandem mass spectrometry. Logistic regression modeling estimated the association of each metabolite with development of PE.

RESULTS

We compared 41 cases with PE with 41 controls and found four metabolites (hydroxyhexanoylcarnitine, alanine, phenylalanine, and glutamate) that were significantly higher in the cases with PE. The area under the curve (AUC) using these metabolites individually to predict PE varied from 0.77 to 0.80, and when combined, the AUC improved to 0.82 [95% confidence interval (95% CI): 0.80-0.85] for all cases of PE and 0.85 (95% CI: 0.76-0.91) for early onset PE.

CONCLUSION

Our findings suggest a potential role for first-trimester metabolomics in screening for PE.

Metabolic profiling uncovers a phenotypic signature of small for gestational age in early pregnancy

Being born small for gestational age (SGA) confers increased risks of perinatal morbidity and mortality and increases the risk of cardiovascular complications and diabetes in later life. Accumulating evidence suggests that the etiology of SGA is usually associated with poor placental vascular development in early pregnancy. We examined metabolomic profiles using ultra performance liquid chromatography-mass spectrometry (UPLC-MS) in three independent studies: (a) venous cord plasma from normal and SGA babies, (b) plasma from a rat model of placental insufficiency and controls, and (c) early pregnancy peripheral plasma samples from women who subsequently delivered a SGA baby and controls. Multivariate analysis by cross-validated Partial Least Squares Discriminant Analysis (PLS-DA) of all 3 studies showed a comprehensive and similar disruption of plasma metabolism. A multivariate predictive model combining 19 metabolites produced by a Genetic Algorithm-based search program gave an Odds Ratio for developing SGA of 44, with an area under the Receiver Operator Characteristic curve of 0.9. Sphingolipids, phospholipids, carnitines, and fatty acids were among this panel of metabolites. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of SGA offers insight into disease pathogenesis and offers the promise of a robust presymptomatic screening test.

Review: The effects of oxygen on normal and pre-eclamptic placental tissue--insights from metabolomics

Placental dysfunction is central to many complications of human pregnancy including pre-eclampsia (PE), intra-uterine growth restriction (IUGR) and stillbirth. The precise molecular pathophysiology of placental dysfunction in these conditions is not known, although oxidative and nitrative stresses have been implicated. Metabolites are low molecular weight chemicals which play an important role in biological function, primarily through metabolism and regulation of biological processes. The holistic study of metabolites, defined as metabolomics or metabolic profiling, has the objective to detect and identify all, or a large complement of all metabolites. Metabolomics is applied to discover new knowledge regarding biological processes and systems. We hypothesised that a metabolomic strategy could (1) provide a reproducible technique to investigate the intracellular metabolism of placental tissue and also metabolites consumed from or secreted in to the extracellular 'metabolic footprint' of in vitro culture systems (2) identify metabolic related differences in placental tissue culture systems subjected to perturbations in oxygen tension and from pregnancies complicated by PE. We review our early studies which demonstrate that a reproducible experimental protocol is required, including the preparation of culture medium and the site of the placenta applied for sampling tissue. We have detected changes in the intracellular metabolome and metabolic footprint of placental tissue in response to altered oxygen tension and PE. We have demonstrated that placental tissue from uncomplicated pregnancies cultured in 1% oxygen (hypoxia) had metabolic similarities to explants from PE pregnancies cultured at 6% oxygen (normoxia). Metabolites requiring further study include lipids, glutamate and glutamine and metabolites related to tryptophan, leukotriene and prostaglandin metabolism. Metabolomics has the potential to identify changes in clinical conditions, such as PE, that are associated with placental molecular pathophysiology.