Urinary metabolic profiles in early pregnancy are associated with preterm birth and fetal growth restriction in the Rhea mother-child cohort study

Urinary metabolomics reveals potential biomarkers for early detection of pregnancy in Mithun (Bos frontalis) cows

The present study investigated the urinary metabolic profiles of early pregnant and non-pregnant Mithun to identify potential pregnancy detection biomarkers. Urine samples were collected on days 0, 10, 18, 35 and 45 of gestation from pregnant (n = 6) and on days 0, 10 and 18 from non-pregnant (n = 6) Mithun. Urinary metabolites were assessed using proton nuclear magnetic resonance (1H NMR) spectroscopy and identified 270 metabolites. Statistical analyses demonstrated pronounced distinctions in metabolite profiles between pregnant and non-pregnant samples. Twenty-five metabolites that could discriminate between pregnant and non-pregnant Mithun based on Variable Importance in Projection (VIP) scores >1 were identified. Upon further examination of six metabolites (kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine and leucine) identified with high VIP scores, ROC curve analyses demonstrated their significant predictive potential, with AUC values ranging between 0.50 and 0.85. Additionally, a combined panel of top 25 metabolites yielded an AUC value of 0.85. Pathway analysis identified seven potential metabolic pathway modulations during early gestation, with particular emphasis on phenylalanine, tyrosine and tryptophan biosynthesis, tryptophan pathway and pathways involved in the metabolism of various amino acids. In conclusion, kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine, and leucine show promise as non-invasive urinary biomarkers for early pregnancy detection in Mithun. SIGNIFICANCE: This study presents the first report on the metabolic profile of urine from early pregnant and non-pregnant Mithun (Bos frontalis). The metabolites like kynurenine and its derivatives (kynurenate, 3-hydroxykynurenine and quinolinate), tyrosine and leucine were documented signature urinary metabolites associated with early pregnancy in Mithun. The identified combination of metabolites holds promise as predictive biomarkers for non-invasive urinary-based early pregnancy diagnostics in Mithun. In addition, this study identified changes in metabolic pathways that involve phenylalanine, tyrosine, tryptophan and related amino acids and biomarkers identified were either precursors or products within these metabolic pathways.

Investigation of newborn blood metabolomics in varying intrauterine growth conditions

OBJECTIVES

This study aimed to investigate changes in the blood metabolic profiles of newborns with varying intrauterine growth conditions. Specifically, we analyzed the levels of amino acids, carnitine, and succinylacetone among full-term newborns, including small for gestational age (SGA), appropriate for gestational age (AGA), and large for gestational age (LGA). We aim to identify differential metabolites and metabolic pathways that may offer insights into clinical interventions.

METHODS

A total of 5106 full-term newborns were included in the study. Blood samples were obtained from all newborns between 3 and 5 days after birth and analyzed using tandem mass spectrometry to detect blood metabolites. Subsequently, we screened for different metabolites and metabolic pathways among the groups using the MetaboAnalystR package (Version 1.0.1) in R software (R-3.6.0).

RESULTS

The levels of blood amino acids and carnitine metabolism differed significantly among newborns with varying intrauterine growth conditions. Full-term SGA newborns exhibited a decrease in multiple amino acids and an increase in multiple carnitines, while full-term LGA newborns showed an increase in multiple amino acids and acylcarnitines.

CONCLUSION

Continuous monitoring of the short-term and long-term growth and metabolic status of full-term SGA and LGA newborns is warranted with individualized dietary and nutritional adjustments to promote healthy growth in a timely manner. The findings of this research contribute to the broader understanding of SGA/LGA and shall inform future research on metabolomics, interventions, and long-term outcomes.

Prenatal and Early Life Exposure to Ambient Air Pollutants Is Associated with the Fecal Metabolome in the First Two Years of Life

Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

Ambient air pollution and adverse birth outcomes: A review of underlying mechanisms

Epidemiological data provide varying degrees of evidence for associations between prenatal exposure to ambient air pollutants and adverse birth outcomes (suboptimal measures of fetal growth, preterm birth and stillbirth). To assess further certainty of effects, this review examines the experimental literature base to identify mechanisms by which air pollution (particulate matter, nitrogen dioxide and ozone) could cause adverse effects on the developing fetus. It likely that this environmental insult impacts multiple biological pathways important for sustaining a healthy pregnancy, depending upon the composition of the pollutant mixture and the exposure window owing to changes in physiologic maturity of the placenta, its circulations and the fetus as pregnancy ensues. The current body of evidence indicates that the placenta is a target tissue, impacted by a variety of critical processes including nitrosative/oxidative stress, inflammation, endocrine disruption, epigenetic changes, as well as vascular dysregulation of the maternal-fetal unit. All of the above can disturb placental function and, as a consequence, could contribute to compromised fetal growth as well increasing the risk of stillbirth. Furthermore, given that there is often an increased inflammatory response associated with preterm labour, inflammation is a plausible mechanism mediating the effects of air pollution on premature delivery. In the light of increased urbanisation and an ever-changing climate, both of which increase ambient air pollution and negatively affect vulnerable populations such as pregnant individuals, it is hoped that the collective evidence may contribute to decisions taken to strengthen air quality policies, reductions in exposure to air pollution and subsequent improvements in the health of those not yet born.

How do mothers with young children perceive endocrine-disrupting chemicals?: an exploratory qualitative study

PURPOSE

Despite the health impacts of endocrine-disrupting chemicals (EDCs) beginning in the early stages of life, there is little research on the perception of EDCs among Korean mothers, who are primarily responsible for protecting children. This study aimed to explore how mothers with young children perceived EDCs for their concerns, the issues they faced, and the way they dealt with them.

METHODS

An exploratory qualitative design was utilized. Twelve mothers who were recruited from snowball sampling participated in voluntary interviews. Individual in-depth interviews lasting approximately 47 to 60 minutes were recorded and transcribed verbatim. The data were analyzed using qualitative content analysis as suggested by Graneheim and Lundman.

RESULTS

Four categories, 10 subcategories, and 25 condensed meaning units were identified by interpreting mothers' underlying meanings. The four categories were 'Knowledgeable yet contrasting ideas regarding EDCs,' 'Negative health impact, but more so for children,' 'Inaction or trying to minimize exposure,' and 'Need for early, reliable resources and social change.' Mothers were knowledgeable about EDCs and actively needed further education and support. While they tended to focus more on the health impact of EDCs on their children and were optimistic about their health risks, paying less attention to their preventive behaviors.

CONCLUSION

Healthcare professionals must consider mothers' perceptions of EDCs in future education and interventions regarding EDCs impact on women's life stages such as puberty, pregnancy, and childrearing. Also preventive strategies that can be applied to their daily lives are needed.

The roles of trimethylamine-N-oxide in atherosclerosis and its potential therapeutic aspect: A literature review

Current research supports the evidence that the gut microbiome (GM), which consist of gut microbiota and their biologically active metabolites, is associated with atherosclerosis development. Trimethylamine-N-oxide (TMAO), a metabolite produced by the GM through trimethylamine (TMA) oxidation, significantly enhances the formation and vulnerability of atherosclerotic plaques. TMAO promotes inflammation and oxidative stress in endothelial cells, leading to vascular dysfunction and plaque formation. Dimethyl-1-butanol (DMB), iodomethylcholine (IMC) and fluoromethylcholine (FMC) have been recognized for their ability to reduce plasma TMAO by inhibiting trimethylamine lyase, a bacterial enzyme involved in the choline cleavage anaerobic process, thus reducing TMA formation. Conversely, indole-3-carbinol (I3C) and trigonelline inhibit TMA oxidation by inhibiting flavin-containing monooxygenase-3 (FMO3), resulting in reduced plasma TMAO. The combined use of inhibitors of choline trimethylamine lyase and flavin-containing monooxygenase-3 could provide novel therapeutic strategies for cardiovascular disease prevention by stabilizing existing atherosclerotic plaques. This review aims to present the current evidence of the roles of TMA/TMAO in atherosclerosis as well as its potential therapeutic prevention aspects.

Metabolomics can provide new insights into perinatal nutrition

Perinatal nutrition is a key factor related to the Developmental Origin of Health and Disease hypothesis, which states that each and every event that happens during the periconceptional period and pregnancy can affect the health status of an individual. Metabolomics can be a very useful tool for gathering information about the effect of perinatal nutrition on both mothers and newborn infants. This non-systematic review focuses on the main metabolites detected by this technique, with regard to gestational diabetes, intrauterine growth restriction and breast milk. Conclusion. Nutrition, metabolome and microbiome interactions are gaining interest in the scientific community.

Exploration of urinary metabolite dynamicity for early detection of pregnancy in water buffaloes

Early and precise pregnancy diagnosis can reduce the calving interval by minimizing postpartum period. The present study explored the differential urinary metabolites between pregnant and non-pregnant Murrah buffaloes (Bubalus bubalis) during early gestation to identify potential pregnancy detection biomarkers. Urine samples were collected on day 0, 10, 18, 35 and 42 of gestation from the pregnant (n = 6) and on day 0, 10 and 18 post-insemination from the non-pregnant (n = 6) animals. ¹H-NMR-based untargeted metabolomics followed by multivariate analysis initially identified twenty-four differentially expressed metabolites, among them 3-Hydroxykynurenine, Anthranilate, Tyrosine and 5-Hydroxytryptophan depicted consistent trends and matched the selection criteria of potential biomarkers. Predictive ability of these individual biomarkers through ROC curve analyses yielded AUC values of 0.6–0.8. Subsequently, a logistic regression model was constructed using the most suitable metabolite combination to improve diagnostic accuracy. The combination of Anthranilate, 3-Hydroxykynurenine, and Tyrosine yielded the best AUC value of 0.804. Aromatic amino acid biosynthesis, Tryptophan metabolism, Phenylalanine and Tyrosine metabolism were identified as potential pathway modulations during early gestation. The identified biomarkers were either precursors or products of these metabolic pathways, thus justifying their relevance. The study facilitates precise non-invassive urinary metabolite-based pen-side early pregnancy diagnostics in buffaloes, eminently before 21 days post-insemination.

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.

Compartmentalized regulation of NAD+ by Di (2-ethyl-hexyl) phthalate induces DNA damage in placental trophoblast

Di (2-ethyl-hexyl) phthalate (DEHP) is a wildly used plasticizer. Maternal exposure to DEHP during pregnancy blocks the placental cell cycle at the G2/M phase by reducing the efficiency of the DNA repair pathways and affects the health of offsprings. However, the mechanism by which DEHP inhibits the repair of DNA damage remains unclear. In this study, we demonstrated that DEHP inhibits DNA damage repair by reducing the activity of the DNA repair factor recruitment molecule PARP1. NAD+ and ATP are two substrates necessary for PARP1 activity. DEHP abated NAD+ in the nucleus by reducing the level of NAD+ synthase NMNAT1 and elevated NAD+ in the mitochondrial by promoting synthesis. Furthermore, DEHP destroyed the mitochondrial respiratory chain, affected the structure and quantity of mitochondria, and decreased ATP production. Therefore, DEHP inhibits PARP1 activity by reducing the amount of NAD+ and ATP, which hinders the DNA damage repair pathways. The supplement of NAD+ precursor NAM can partially rescue the DNA and mitochondria damage. It provides a new idea for the prevention of health problems of offsprings caused by DEHP injury to the placenta.

Systematic review of preterm birth multi-omic biomarker studies

Preterm birth (PTB) is one of the leading causes of deaths in infants under the age of five. Known risk factors of PTB include genetic factors, lifestyle choices or infection. Identification of omic biomarkers associated with PTB could aid clinical management of women at high risk of early labour and thereby reduce neonatal morbidity. This systematic literature review aimed to identify and summarise maternal omic and multi-omic (genomics, transcriptomics, proteomics and metabolites) biomarker studies of PTB. Original research articles were retrieved from three databases: PubMed, Web of Science and Science Direct, using specified search terms for each omic discipline. PTB studies investigating genomics, transcriptomics, proteomics or metabolomics biomarkers prior to onset of labour were included. Data were collected and reviewed independently. Pathway analyses were completed on the biomarkers from non-targeted omic studies using Reactome pathway analysis tool. A total of 149 omic studies were identified; most of the literature investigated proteomic biomarkers. Pathway analysis identified several cellular processes associated with the omic biomarkers reported in the literature. Study heterogeneity was observed across the research articles, including the use of different gestation cut-offs to define PTB. Infection/inflammatory biomarkers were identified across majority of papers using a range of targeted and non-targeted approaches.

Balancing the Equation: A Natural History of Trimethylamine and Trimethylamine-N-oxide

Trimethylamine (TMA) and its N-oxide (TMAO) are ubiquitous in prokaryote and eukaryote organisms as well as in the environment, reflecting their fundamental importance in evolutionary biology, and their diverse biochemical functions. Both metabolites have multiple biological roles including cell-signaling. Much attention has focused on the significance of serum and urinary TMAO in cardiovascular disease risk, yet this is only one of the many facets of a deeper TMA-TMAO partnership that reflects the significance of these metabolites in multiple biological processes spanning animals, plants, bacteria, and fungi. We report on analytical methods for measuring TMA and TMAO and attempt to critically synthesize and map the global functions of TMA and TMAO in a systems biology framework.

Associations of maternal and infant metabolite profiles with foetal growth and the odds of adverse birth outcomes

BACKGROUND

Adaptations in maternal and foetal metabolic pathways may predispose to altered foetal growth and adverse birth outcomes.

OBJECTIVE

To assess the associations of maternal early-pregnancy metabolite profiles and infant metabolite profiles at birth with foetal growth from first trimester onwards and the odds of adverse birth outcomes.

METHODS

In a prospective population-based cohort among 976 Dutch pregnant women and their children, serum concentrations of amino acids, non-esterified fatty acids (NEFA), phospholipids (PL) and carnitines in maternal early-pregnancy blood and in cord blood were obtained by liquid-chromatography tandem mass spectrometry. Information on foetal growth was available from first trimester onwards.

RESULTS

After false discovery rate correction for multiple testing, higher infant total and individual NEFA concentrations were associated with a lower weight, length, and head circumference at birth. Higher infant total and individual acyl-lysophosphatidylcholine (lyso.PC.a) and alkyl-lysophosphatidylcholine concentrations were associated with higher weight and head circumference (lyso.PC.a only) at birth, higher odds of LGA and lower odds of SGA. Few individual maternal metabolites were associated with foetal growth measures in third trimester and at birth, but not with the odds of adverse birth outcomes.

CONCLUSIONS

Our results suggest that infant metabolite profiles, particularly total and individual lyso.PC.a and NEFA concentrations, were strongly related to growth measures at birth and the odds of adverse birth outcomes. Few individual maternal early-pregnancy metabolites, but not total metabolite concentrations, are associated with foetal growth measures in third trimester and at birth.

Regulatory Effect of Resveratrol on Inflammation Induced by Lipopolysaccharides via Reprograming Intestinal Microbes and Ameliorating Serum Metabolism Profiles

The purpose of this study was to explore the regulatory effect of resveratrol (RES) on lipopolysaccharide (LPS)-induced inflammation and its influence on intestinal microorganisms and serum atlas in murine models during the development of inflammation to explore a novel method for the regulation of inflammation. Mice were randomly assigned to three groups: control (CON), LPS, and RES–LPS. The results showed that RES mitigated the inflammatory damage to the intes-tines and liver induced by LPS. Compared with the LPS group, RES treatment decreased the levels of TNF-α, IL-6, IFN-γ, myeloperoxidase, and alanine aminotransferase in the liver. Serum metabolic profile monitoring showed that, compared with the CON group, LPS decreased the levels of five metabolites, including cycloartomunin and glycerol triundecanoate, and increased the levels of eight metabolites, including N-linoleoyl taurine and PE(O-16:0/20:5(5Z), 8Z, 11Z, 14Z, 17Z). Conversely, RES treatment increased the levels of eight metabolites, including pantothenic acid, homovanillic acid, and S-(formylmethyl)glutathione, and reduced seven metabolites, including lysoPE(20:4(8Z,11Z,14Z,17Z)/0:0) and 13-cis-retinoic acid, etc., in comparison with the LPS group. Moreover, RES treatment alleviated the negative effects of LPS on intestinal microbes by reducing, for instance, the relative abundance of Bacteroidetes and Alistipes, and increasing the relative abundance of Lactobacillus. These results suggest that RES has great potential for preventing in-flammation.

Non-linear and non-additive associations between the pregnancy metabolome and birthweight

BACKGROUND

Birthweight is an indicator of fetal growth and environmental-related alterations of birthweight have been linked with multiple disorders and conditions progressing into adulthood. Although a few studies have assessed the association between birthweight and the totality of exogenous exposures and their downstream molecular responses in maternal urine and cord blood; no prior research has considered a) the maternal serum prenatal metabolome, which is enriched for hormones, and b) non-linear and synergistic associations among exposures.

METHODS

We measured the maternal serum metabolome during pregnancy using an untargeted metabolomics approach and birthweight for gestational age (BWGA) z-score in 410 mother-child dyads enrolled in the PRogramming of Intergenerational Stress Mechanisms (PRISM) cohort. We leveraged a Bayesian factor analysis for interaction to select the most important metabolites associated with BWGA z-score and to evaluate their linear, non-linear and non-additive associations. We also assessed the primary biological functions of the identified proteins using the MetaboAnalyst, a centralized repository of curated functional information. We compared our findings with those of a traditional metabolite-wide association study (MWAS) in which metabolites are individually associated with BWGA z-score.

RESULTS

Among 1110 metabolites, 46 showed evidence of U-shape associations with BWGA z-score. Most of the identified metabolites (85%) were lipids primarily enriched for pathways central to energy production, immune function, and androgen and estrogen metabolism, which are essential for pregnancy and parturition processes. Metabolites within the same class, i.e. steroids and phospholipids, showed synergistic relationships with each other.

CONCLUSIONS

Our results support that the aspects of the maternal metabolome during pregnancy contribute linearly, non-linearly and synergistically to variation in newborn birthweight.

Metabolic profiling of maternal serum of women at high-risk of spontaneous preterm birth using NMR and MGWAS approach

Preterm birth (PTB) is a leading global cause of infant mortality. Risk factors include genetics, lifestyle choices and infection. Understanding the mechanism of PTB could aid the development of novel approaches to prevent PTB. This study aimed to investigate the metabolic biomarkers of PTB in early pregnancy and the association of significant metabolites with participant genotypes. Maternal sera collected at 16 and 20 weeks of gestation, from women who previously experienced PTB (high-risk) and women who did not (low-risk controls), were analysed using 1H nuclear magnetic resonance (NMR) metabolomics and genome-wide screening microarray. ANOVA and probabilistic neural network (PNN) modelling were performed on the spectral bins. Metabolomics genome-wide association (MGWAS) of the spectral bins and genotype data from the same participants was applied to determine potential metabolite-gene pathways. Phenylalanine, acetate and lactate metabolite differences between PTB cases and controls were obtained by ANOVA and PNN showed strong prediction at week 20 (AUC = 0.89). MGWAS identified several metabolite bins with strong genetic associations. Cis-eQTL analysis highlighted TRAF1 (involved in the inflammatory pathway) local to a non-coding SNP associated with lactate at week 20 of gestation. MGWAS of a well-defined cohort of participants highlighted a lactate-TRAF1 relationship that could potentially contribute to PTB.

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

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

Molecular Mechanism of Microbiota Metabolites in Preterm Birth: Pathological and Therapeutic Insights

Preterm birth (PTB) refers to the birth of infants before 37 weeks of gestation and is a challenging issue worldwide. Evidence reveals that PTB is a multifactorial dysregulation mediated by a complex molecular mechanism. Thus, a better understanding of the complex molecular mechanisms underlying PTB is a prerequisite to explore effective therapeutic approaches. During early pregnancy, various physiological and metabolic changes occur as a result of endocrine and immune metabolism. The microbiota controls the physiological and metabolic mechanism of the host homeostasis, and dysbiosis of maternal microbial homeostasis dysregulates the mechanistic of fetal developmental processes and directly affects the birth outcome. Accumulating evidence indicates that metabolic dysregulation in the maternal or fetal membranes stimulates the inflammatory cytokines, which may positively progress the PTB. Although labour is regarded as an inflammatory process, it is still unclear how microbial dysbiosis could regulate the molecular mechanism of PTB. In this review based on recent research, we focused on both the pathological and therapeutic contribution of microbiota-generated metabolites to PTB and the possible molecular mechanisms.

Associations of prenatal metabolomics profiles with early childhood growth trajectories and obesity risk in African Americans: the CANDLE study

OBJECTIVE

Prenatal metabolomics profiles, providing measures of in utero nutritional and environmental exposures, may improve the prediction of childhood outcomes. We aimed to identify prenatal plasma metabolites associated with early childhood body mass index (BMI) trajectories and overweight/obesity risk in offspring.

METHODS

This study included 450 African American mother-child pairs from the Conditions Affecting Neurocognitive Development and Learning in Early Childhood Study. An untargeted metabolomics analysis was performed on the mothers' plasma samples collected during the second trimester. The children's BMI-z-score trajectories from birth to age 4 [rising-high- (9.8%), moderate- (68.2%), and low-BMI (22.0%)] and overweight/obesity status at age 4 were the main outcomes. The least absolute shrinkage and selection operator (LASSO) was used to select the prenatal metabolites associated with childhood outcomes.

RESULTS

The mothers were 24.5 years old on average at recruitment, 76.4% having education less than 12 years and 80.0% with Medicaid or Medicare. In LASSO, seven and five prenatal metabolites were associated with the BMI-z-score trajectories and overweight/obese at age 4, respectively. These metabolites are mainly from/relevant to the pathways of steroid biosynthesis, amino acid metabolism, vitamin B complex, and xenobiotics metabolism (e.g., caffeine and nicotine). The odds ratios (95% CI) associated with a one SD increase in the prenatal metabolite risk scores (MRSs) constructed from the LASSO-selected metabolites were 2.97 (1.95-4.54) and 2.03 (1.54-2.67) for children being in the rising-high-BMI trajectory group and overweight/obesity at age 4, respectively. The MRSs significantly improved the risk prediction for childhood outcomes beyond traditional prenatal risk factors. The increase (95% CI) in the area under the receiver operating characteristic curves were 0.10 (0.03-0.18) and 0.07 (0.02-0.12) for the rising-high-BMI trajectory (P = 0.005) and overweight/obesity at age 4 (P = 0.007), respectively.

CONCLUSIONS

Prenatal metabolomics profiles advanced prediction of early childhood growth trajectories and obesity risk in offspring.

Glycerophospholipid and detoxification pathways associated with small for gestation age pathophysiology: discovery metabolomics analysis in the SCOPE cohort

INTRODUCTION

Small for gestational age (SGA) may be associated with neonatal morbidity and mortality. Our understanding of the molecular pathways implicated is poor.

OBJECTIVES

Our aim was to determine the metabolic pathways involved in the pathophysiology of SGA and examine their variation between maternal biofluid samples.

METHODS

Plasma (Cork) and urine (Cork, Auckland) samples were collected at 20 weeks' gestation from nulliparous low-risk pregnant women participating in the SCOPE study. Women who delivered an SGA infant (birthweight < 10th percentile) were matched to controls (uncomplicated pregnancies). Metabolomics (urine) and lipidomics (plasma) analyses were performed using ultra performance liquid chromatography-mass spectrometry. Features were ranked based on FDR adjusted p-values from empirical Bayes analysis, and significant features putatively identified.

RESULTS

Lipidomics plasma analysis revealed that 22 out of the 33 significantly altered lipids annotated were glycerophospholipids; all were detected in higher levels in SGA. Metabolomic analysis identified reduced expression of metabolites associated with detoxification (D-Glucuronic acid, Estriol-16-glucuronide), nutrient absorption and transport (Sulfolithocholic acid) pathways.

CONCLUSIONS

This study suggests higher levels of glycerophospholipids, and lower levels of specific urine metabolites are implicated in the pathophysiology of SGA. Further research is needed to confirm these findings in independent samples.

The Potential of Metabolomic Analyses as Predictive Biomarkers of Preterm Delivery: A Systematic Review

SCOPE

as the leading cause of perinatal mortality and morbidity worldwide, the impact of premature delivery is undisputable. Thus far, non-invasive, cost-efficient and accurate biochemical markers to predict preterm delivery are scarce. The aim of this systematic review is to investigate the potential of non-invasive metabolomic biomarkers for the prediction of preterm delivery.

METHODS AND RESULTS

Databases were systematically searched from March 2019 up to May 2020 resulting in 4062 articles, of which 45 were retrieved for full-text assessment. The resulting metabolites used for further analyses, such as ferritin, prostaglandin and different vitamins were obtained from different human anatomical compartments or sources (vaginal fluid, serum, urine and umbilical cord) and compared between groups of women with preterm and term delivery. None of the reported metabolites showed uniform results, however, a combination of metabolomics biomarkers may have potential to predict preterm delivery and need to be evaluated in future studies.

Metabolic dysfunction in pregnancy: Fingerprinting the maternal metabolome using proton nuclear magnetic resonance spectroscopy

Aims

Maternal metabolic disorders place the mother at risk for negative pregnancy outcomes with potentially long-term health impacts for the child. Metabolic syndrome, a cluster of features associated with increased risk of metabolic disorders, such as cardiovascular disease, diabetes and stroke, affects roughly one in five Canadians. Metabolomics is a relatively new technique that may be a useful tool to identify women at risk of metabolic disorders. This study set out to characterize urinary metabolic biomarkers of pregnant women with obesity and of pregnant women who later developed gestational diabetes mellitus (pre-GDM), compared to controls.

Methods and Materials

Second trimester urine samples were collected through the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort and examined with 1H nuclear magnetic resonance (NMR) spectroscopy. Multivariate analysis was used to examine group differences, and machine learning feature selection tools identified the metabolites contributing to separation.

Results

Obesity and pre-GDM metabolomes were distinct from controls and from each other. In each comparison, the glycine, serine and threonine pathways were the most impacted. Pantothenate, formic acid and glycine were downregulated by obesity, while formic acid, dimethylamine and galactose were downregulated in pre-GDM. The three most impacted metabolites for the comparison of obesity versus pre-GDM groups were upregulated creatine/caffeine, downregulated sarcosine/dimethylamine and upregulated maltose/sucrose in individuals who later developed GDM.

Conclusion

These findings suggest a role for urinary metabolomics in the prediction of GDM and metabolic marker identification for potential diagnostics and prognostics in women at risk.

Metabolic Signatures of Gestational Weight Gain and Postpartum Weight Loss in a Lifestyle Intervention Study of Overweight and Obese Women

Background: Overweight and obesity amongst women of reproductive age are increasingly common in developed economies and are shown to adversely affect birth outcomes and both childhood and adulthood health risks in the offspring. Metabolic profiling in conditions of overweight and obesity in pregnancy could potentially be applied to elucidate the molecular basis of the adverse effects of gestational weight gain (GWG) and postpartum weight loss (WL) on future risks for cardiovascular disease (CVD) and other chronic diseases. Methods: Biofluid samples were collected from 114 ethnically diverse pregnant women with body mass index (BMI) between 25 and 40 kg/m² from Chicago (US), as part of a randomized lifestyle intervention trial (Maternal Offspring Metabolics: Family Intervention Trial; NCT01631747). At 15 weeks, 35 weeks of gestation, and at 1 year postpartum, the blood plasma lipidome and metabolic profile of urine samples were analyzed by liquid chromatography mass spectrometry (LC-MS) and ¹H nuclear magnetic resonance spectroscopy (¹H NMR) respectively. Results: Urinary 4-deoxyerythronic acid and 4-deoxythreonic acid were found to be positively correlated to BMI. Seventeen plasma lipids were found to be associated with GWG and 16 lipids were found to be associated with WL, which included phosphatidylinositols (PI), phosphatidylcholines (PC), lysophospholipids (lyso-), sphingomyelins (SM) and ether phosphatidylcholine (PC-O). Three phospholipids found to be positively associated with GWG all contained palmitate side-chains, and amongst the 14 lipids that were negatively associated with GWG, seven were PC-O. Six of eight lipids found to be negatively associated with WL contained an 18:2 fatty acid side-chain. Conclusions: Maternal obesity was associated with characteristic urine and plasma metabolic phenotypes, and phospholipid profile was found to be associated with both GWG and postpartum WL in metabolically healthy pregnant women with overweight/obesity. Postpartum WL may be linked to the reduction in the intake of linoleic acid/conjugated linoleic acid food sources in our study population.

Prenatal Exposure to Multiple Air Pollutants, Mediating Molecular Mechanisms, and Shifts in Birthweight

Mechanisms underlying adverse birth and later in life health effects from exposure to air pollution during the prenatal period have not been not fully elucidated, especially in the context of mixtures. We assessed the effects of prenatal exposure to mixtures of air pollutants of particulate matter (PM), PM2.5, PM10, nitrogen oxides, NO2, NOx, ultrafine particles (UFP), and oxidative potential (OP) of PM2.5 on infant birthweight in four European birth cohorts and the mechanistic underpinnings through cross-omics of metabolites and inflammatory proteins. The association between mixtures of air pollutants and birthweight z-scores (standardized for gestational age) was assessed for three different mixture models, using Bayesian machine kernel regression (BKMR). We determined the direct effect for PM2.5, PM10, NO2, and mediation by cross-omic signatures (identified using sparse partial least-squares regression) using causal mediation BKMR models. There was a negative association with birthweight z-scores and exposure to mixtures of air pollutants, where up to -0.21 or approximately a 96 g decrease in birthweight, comparing the 75th percentile to the median level of exposure to the air pollutant mixture could occur. Shifts in birthweight z-scores from prenatal exposure to PM2.5, PM10, and NO2 were mediated by molecular mechanisms, represented by cross-omics scores. Interleukin-17 and epidermal growth factor were identified as important inflammatory responses underlyingair pollution-associated shifts in birthweight. Our results signify that by identifying mechanisms through which mixtures of air pollutants operate, the causality of air pollution-associated shifts in birthweight is better supported, substantiating the need for reducing exposure in vulnerable populations.

Diabetes Leads to Alterations in Normal Metabolic Transitions of Pregnancy as Revealed by Time-Course Metabolomics

Women with diabetes during pregnancy are at increased risk of poor maternal and neonatal outcomes. Despite this, the effects of pre-gestational (PGDM) or gestational diabetes (GDM) on metabolism during pregnancy are not well understood. In this study, we utilized metabolomics to identify serum metabolic changes in women with and without diabetes during pregnancy and the cord blood at birth. We observed elevations in tricarboxylic acid (TCA) cycle intermediates, carbohydrates, ketones, and lipids, and a decrease in amino acids across gestation in all individuals. In early gestation, PGDM had elevations in branched-chain amino acids and sugars compared to controls, whereas GDM had increased lipids and decreased amino acids during pregnancy. In both GDM and PGDM, carbohydrate and amino acid pathways were altered, but in PGDM, hemoglobin A1c and isoleucine were significantly increased compared to GDM. Cord blood from GDM and PGDM newborns had similar increases in carbohydrates and choline metabolism compared to controls, and these alterations were not maternal in origin. Our results revealed that PGDM and GDM have distinct metabolic changes during pregnancy. A better understanding of diabetic metabolism during pregnancy can assist in improved management and development of therapeutics and help mitigate poor outcomes in both the mother and newborn.

Antenatal Care Attendance and Factors Influenced Birth Weight of Babies Born between June 2017 and May 2018 in the Wa East District, Ghana

Background

In sub-Saharan Africa, there is high coverage of the recommended four or more times antenatal care (ANC) visits during pregnancy without complications; notwithstanding this achievement, the negative birth outcomes related to childbirth such as low birth weights and stillbirths are still high despite the increased access to antenatal services. Hence, the study assessed the association between antenatal attendance and birth weight in the Wa East District.

Method

The cross-sectional study design was used with a semistructured questionnaire to collect data from mothers who delivered within a one-year period through a review of antenatal and birth records from health facilities where the women delivered and interviewed. The chi-squared test and univariate and multivariate logistic regression were performed to establish the association between normal birth weight and ANC services the woman received and other predictor variables, and p value < 0.05 was considered a significant association between dependent and independent variables.

Result

The study involved 233 women. About 62.2% attended ANC clinics 4+ times before giving birth, 70.0% did not received the minimum ANC services required for every pregnant woman, 0.9% of pregnancies resulted in stillbirth, and 24.5% of babies born had a birth weight < 2.5 kg. Women marital status (legally married) [AOR: 2.05, 95% CI: 1.33-6.89, p = 0.044], religion (Islam) [AOR: 0.33, 95% CI: 0.08-0.39, p = 0.013], and educational level (SHS/tertiary) [AOR: 4.27, 95% CI: 0.08-0.88, p = 0.031] were the background characteristics associated with normal birth weight (2.5-40 kg). Also, women who had their urine tested at the ANC clinics [AOR: 6.59, 95% CI: 8.48–15.07, p < 0.001] and women who received a long-lasting insecticide-treated net [AOR: 2.17, 95% CI: 0.03-0.92, p = 0.039] from the ANC clinic were associated with normal birth weight.

Conclusion

Notwithstanding the benefits of antenatal care services, only 62.2% of pregnant women attended 4 or more ANC visits before giving birth, while 70% did not received the services they need. These might have influence the 24.5% of babies born with a low birth weight. Therefore, there is a need for special attention from all stakeholders to reverse the trend.

Maternal plasma metabolic markers of neonatal adiposity and associated maternal characteristics: The GUSTO study

Infant adiposity may be related to later metabolic health. Maternal metabolite profiling reflects both genetic and environmental influences and allows elucidation of metabolic pathways associated with infant adiposity. In this multi-ethnic Asian cohort, we aimed to (i) identify maternal plasma metabolites associated with infant adiposity and other birth outcomes and (ii) investigate the maternal characteristics associated with those metabolites. In 940 mother-offspring pairs, we performed gas chromatography-mass spectrometry and identified 134 metabolites in maternal fasting plasma at 26–28 weeks of gestation. At birth, neonatal triceps and subscapular skinfold thicknesses were measured by trained research personnel, while weight and length measures were abstracted from delivery records. Gestational age was estimated from first-trimester dating ultrasound. Associations were assessed by multivariable linear regression, with p-values corrected using the Benjamini-Hochberg approach. At a false discovery rate of 5%, we observed associations between 28 metabolites and neonatal sum of skinfold thicknesses (13 amino acid-related, 4 non-esterified fatty acids, 6 xenobiotics, and 5 unknown compounds). Few associations were observed with gestational duration, birth weight, or birth length. Maternal ethnicity, pre-pregnancy BMI, and diet quality during pregnancy had the strongest associations with the specific metabolome related to infant adiposity. Further studies are warranted to replicate our findings and to understand the underlying mechanisms.

Human Milk Oligosaccharides Modulate the Risk for Preterm Birth in a Microbiome-Dependent and -Independent Manner

The causes for preterm birth (PTB) often remain elusive. We investigated whether circulating human milk oligosaccharides (HMOs) might be involved in modulating urinary and vaginal microbiome promoting or preventing PTB. We identified here HMOs and key microbial taxa associated with indicators of PTB. Based on our results, we propose two models for how HMOs might modulate risk for PTB: (i) by changes in HMOs associated with sterile inflammation (microbiome-independent) and (ii) by HMO-driven shifts in microbiome (microbiome-dependent). Our findings will guide current efforts to better predict the risk for PTB in seemingly healthy pregnant women and also provide appropriate preventive strategies.

Preterm birth (PTB) is one of the leading causes of neonatal mortality. The causes for spontaneous PTB are multifactorial and often remain unknown. In this study, we tested the hypothesis that human milk oligosaccharides (HMOs) in blood and urine modulate the maternal urinary and vaginal microbiome and influence the risk for PTB. We analyzed the vaginal and urinary microbiome of a cross-sectional cohort of women with or without preterm labor and correlated our findings with measurements of metabolites and HMOs in urine and blood. We identified several microbial signatures, such as Lactobacillus jensenii, L. gasseri, Ureaplasma sp., and Gardnerella sp., associated with a short cervix, PTB, and/or preterm contractions. In addition, we observed associations between sialylated HMOs, in particular 3′-sialyllactose, with PTB, short cervix, and increased inflammation and confirmed an influence of HMOs on the microbiome profile. Since they identify serum and urinary HMOs and several key microorganisms associated with PTB, our findings point at two distinct processes modulating the risk for PTB. One process seems to be driven by sterile inflammation, characterized by increased concentrations of sialylated HMOs in serum. Another process might be microbiome mediated and potentially associated with specific HMO signatures in urine. Our results support current efforts to improve diagnostics and therapeutic strategies in PTB.

IMPORTANCE The causes for preterm birth (PTB) often remain elusive. We investigated whether circulating human milk oligosaccharides (HMOs) might be involved in modulating urinary and vaginal microbiome promoting or preventing PTB. We identified here HMOs and key microbial taxa associated with indicators of PTB. Based on our results, we propose two models for how HMOs might modulate risk for PTB: (i) by changes in HMOs associated with sterile inflammation (microbiome-independent) and (ii) by HMO-driven shifts in microbiome (microbiome-dependent). Our findings will guide current efforts to better predict the risk for PTB in seemingly healthy pregnant women and also provide appropriate preventive strategies.

Non-targeted urinary metabolomics in pregnancy and associations with fetal growth restriction

Our objective was to identify metabolites associated with fetal growth restriction (FGR) by examining early and late pregnancy differences in non-targeted urinary metabolites among FGR cases and non-FGR controls. An exploratory case-control study within LIFECODES birth cohort was performed. FGR cases (N = 30), defined as birthweight below the 10^th percentile, were matched with controls (N = 30) based on maternal age, race, pre-pregnancy body mass index, and gestational age at delivery. Gas chromatography/electron-ionization mass spectrometry was performed on urine samples collected at 10 and 26 weeks of gestation. Differences in urinary metabolite levels in cases and controls at each time point and between the two time points were calculated and then changes compared across pregnancy. 137 unique urinary metabolites were annotated, and several identified that were higher in cases compared to controls. For example, urinary concentrations of benzoic acid were higher in cases compared to controls at both study visits (3.01-fold higher in cases at visit 1, p < 0.01; 3.10-fold higher in cases at visit 3, p = 0.05). However, these findings from our exploratory analysis were not robust to false-discovery-rate adjustment. In conclusion, using a high-resolution, non-targeted approach, we found specific urinary organic acids differed over pregnancy by FGR case status.

Formate metabolism in health and disease

BACKGROUND

Formate is a one-carbon molecule at the crossroad between cellular and whole body metabolism, between host and microbiome metabolism, and between nutrition and toxicology. This centrality confers formate with a key role in human physiology and disease that is currently unappreciated.

SCOPE OF REVIEW

Here we review the scientific literature on formate metabolism, highlighting cellular pathways, whole body metabolism, and interactions with the diet and the gut microbiome. We will discuss the relevance of formate metabolism in the context of embryonic development, cancer, obesity, immunometabolism, and neurodegeneration.

MAJOR CONCLUSIONS

We will conclude with an outlook of some open questions bringing formate metabolism into the spotlight.

The SLC25A42 Transcript Is a Biomarker for Fetal Reprogramming in Response to Placental Insufficiency in Preterm Newborns Under 32 Weeks Gestation-A Pilot Study

Introduction: Timing of medical delivery of preterm newborns exposed to placental insufficiency is largely determined by umbilical artery blood flow and maternal clinical manifestations. There is a lack of tools to properly assess fetal body response to placental insufficiency before or upon delivery. Yet, short- and long-term comorbidities associated with placental insufficiency and the consequential intrauterine growth restriction may be a result of fetal response following prolonged stress. This study aims to establish a procedure to investigate fetal/neonatal transcriptional response to placental insufficiency as part of an initiative to identify cost-effective biomarkers for assessing fetal response to placental insufficiency. Methods: A prospective pilot study involving newborns with birth gestation <32 weeks was conducted to compare gene expression profiles in whole blood collected at birth among three clinically distinct groups - preeclampsia without placental insufficiency (PE), placental insufficiency (PI), and non-PE/PI groups. Results: Whole blood from 11, 3, and 6 newborns in the non-PE/PI, PE, and PI groups were obtained. A transcriptome analysis found that the majority of the genes were downregulated in the PI group, suggesting global transcriptional inactivation. Intriguingly, SLC25A42, which encodes a mitochondrial transporter for coenzyme A and adenosine-3',5'-diphosphate, was significantly upregulated in the PI group. Conclusion: Transcriptional biomarkers for assessing fetal response to placental insufficiency may provide a useful tool to better understand the pathophysiology of fetal reprogramming in response to placental insufficiency. The validity and the role of SLC25A42, as well as its correlation with short- and long-term neonatal outcomes, warrants further investigation.

Fifteen years of epidemiology in BMC Medicine

BMC Medicine was launched in November 2003 as an open access, open peer-reviewed general medical journal that has a broad remit to publish "outstanding and influential research in all areas of clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities". Here, I discuss the last 15 years of epidemiological research published by BMC Medicine, with a specific focus on how this reflects changes occurring in the field of epidemiology over this period; the impact of 'Big Data'; the reinvigoration of debates about causality; and, as we increasingly work across and with many diverse disciplines, the use of the name 'population health science'. Reviewing all publications from the first volume to the end of 2018, I show that most BMC Medicine papers are epidemiological in nature, and the majority of them are applied epidemiology, with few methodological papers. Good research must address important translational questions that should not be driven by the increasing availability of data, but should take appropriate advantage of it. Over the next 15 years it would be good to see more publications that integrate results from several different methods, each with different sources of bias, in a triangulation framework.

Metabolomics to reveal biomarkers and pathways of preterm birth: a systematic review and epidemiologic perspective

INTRODUCTION

Most known risk factors for preterm birth, a leading cause of infant morbidity and mortality, are not modifiable. Advanced molecular techniques are increasingly being applied to identify biomarkers and pathways important in disease development and progression.

OBJECTIVES

We review the state of the literature and assess it from an epidemiologic perspective.

METHODS

PubMed, Embase, CINAHL, and Cochrane Central were searched on January 31, 2019 for original articles published after 1998 that utilized an untargeted metabolomic approach to identify markers of preterm birth. Eligible manuscripts were peer-reviewed and included original data from untargeted metabolomics analyses of maternal tissue derived from human studies designed to determine mechanisms and predictors of preterm birth.

RESULTS

Of 2823 results, 14 articles met the inclusion requirements. There was little consistency in study design, outcome definition, type of biospecimen, or the inclusion of covariates and confounding factors, and few consistent associations with metabolites were identified in this review.

CONCLUSION

Studies to date on metabolomic predictors of preterm birth are highly heterogeneous in both methodology and resulting metabolite identification. There is an urgent need for larger studies in well-defined populations, to determine biomarkers predictive of preterm birth, and to reveal mechanisms and targets for development of intervention strategies.

Blood-based biomarkers in the maternal circulation associated with fetal growth restriction

Fetal growth restriction (FGR) is associated with threefold to fourfold increased risk of stillbirth. Identifying FGR, through its commonly used surrogate-the small-for-gestational-age (SGA, estimated fetal weight and/or abdominal circumference <10th centile) fetus-and instituting fetal surveillance and timely delivery decrease stillbirth risk. Methods available to clinicians for antenatal identification of SGA fetuses have surprisingly poor sensitivity. About 80% of cases remain undetected. Measuring the symphysis-fundal height detects only 20% of SGA fetuses, and even universal third trimester ultrasound detects, at best, 57% of those born SGA. There is an urgent need to find better ways to identify this at-risk cohort. This review summarises efforts to identify molecular biomarkers (proteins, metabolites, or ribonucleic acids) that could be used to better predict FGR. Most studies examining potential biomarkers to date have utilised case-control study designs without proceeding to validation in independent cohorts. To develop a robust test for FGR, large prospective studies are required with a priori validation plans and cohorts. Given that current clinical care detects 20% of SGA fetuses, even a screening test with ≥60% sensitivity at 90% specificity could be clinically useful, if developed. This may be an achievable aspiration. If discovered, such a test may decrease stillbirth.

Integrating -Omics Approaches into Human Population-Based Studies of Prenatal and Early-Life Exposures

PURPOSE OF REVIEW

We present the study design and methodological suggestions for population-based studies that integrate molecular -omics data and highlight recent studies that have used such data to examine the potential impacts of prenatal environmental exposures on fetal health.

RECENT FINDINGS

Epidemiologic studies have observed numerous relationships between prenatal exposures (smoking, toxic metals, endocrine disruptors) and fetal and early-life molecular profiles, though such investigations have so far been dominated by epigenomic association studies. However, recent transcriptomic, proteomic, and metabolomic studies have demonstrated their promise for the identification of exposure and response biomarkers. Molecular -omics have opened new avenues of research in environmental health that can improve our understanding of disease etiology and contribute to the development of exposure and response biomarkers. Studies that incorporate multiple -omics data from different molecular domains in longitudinally collected samples hold particular promise.

Gestational route to healthy birth (GaRBH): protocol for an Indian prospective cohort study

INTRODUCTION

Pregnancy is characterised by a high rate of metabolic shifts from early to late phases of gestation in order to meet the raised physiological and metabolic needs. This change in levels of metabolites is influenced by gestational weight gain (GWG), which is an important characteristic of healthy pregnancy. Inadequate/excessive GWG has short-term and long-term implications on maternal and child health. Exploration of gestational metabolism is required for understanding the quantitative changes in metabolite levels during the course of pregnancy. Therefore, our aim is to study trimester-specific variation in levels of metabolites in relation to GWG and its influence on fetal growth and newborn anthropometric traits at birth.

METHODS AND ANALYSIS

A prospective longitudinal study is planned (start date: February 2018; end date: March 2023) on pregnant women that are being recruited in the first trimester and followed in subsequent trimesters and at the time of delivery (total 3 follow-ups). The study is being conducted in a hospital located in Bikaner district (66% rural population), Rajasthan, India. The estimated sample size is of 1000 mother-offspring pairs. Information on gynaecological and obstetric history, socioeconomic position, diet, physical activity, tobacco and alcohol consumption, depression, anthropometric measurements and blood samples is being collected for metabolic assays in each trimester using standardised methods. Mixed effects regression models will be used to assess the role of gestational weight in influencing metabolite levels in each trimester. The association of maternal levels of metabolites with fetal growth, offspring's weight and body composition at birth will be investigated using regression modelling.

ETHICS AND DISSEMINATION

The study has been approved by the ethics committees of the Department of Anthropology, University of Delhi and Sardar Patel Medical College, Rajasthan. We are taking written informed consent after discussing the various aspects of the study with the participants in the local language.

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).

Trace Amines and Their Receptors

Trace amines are endogenous compounds classically regarded as comprising β-phenylethyalmine, p-tyramine, tryptamine, p-octopamine, and some of their metabolites. They are also abundant in common foodstuffs and can be produced and degraded by the constitutive microbiota. The ability to use trace amines has arisen at least twice during evolution, with distinct receptor families present in invertebrates and vertebrates. The term "trace amine" was coined to reflect the low tissue levels in mammals; however, invertebrates have relatively high levels where they function like mammalian adrenergic systems, involved in "fight-or-flight" responses. Vertebrates express a family of receptors termed trace amine-associated receptors (TAARs). Humans possess six functional isoforms (TAAR1, TAAR2, TAAR5, TAAR6, TAAR8, and TAAR9), whereas some fish species express over 100. With the exception of TAAR1, TAARs are expressed in olfactory epithelium neurons, where they detect diverse ethological signals including predators, spoiled food, migratory cues, and pheromones. Outside the olfactory system, TAAR1 is the most thoroughly studied and has both central and peripheral roles. In the brain, TAAR1 acts as a rheostat of dopaminergic, glutamatergic, and serotonergic neurotransmission and has been identified as a novel therapeutic target for schizophrenia, depression, and addiction. In the periphery, TAAR1 regulates nutrient-induced hormone secretion, suggesting its potential as a novel therapeutic target for diabetes and obesity. TAAR1 may also regulate immune responses by regulating leukocyte differentiation and activation. This article provides a comprehensive review of the current state of knowledge of the evolution, physiologic functions, pharmacology, molecular mechanisms, and therapeutic potential of trace amines and their receptors in vertebrates and invertebrates.

Metabolomics for predicting fetal growth restriction: protocol for a systematic review and meta-analysis

INTRODUCTION

Fetal growth restriction (FGR) is a relevant research and clinical concern since it is related to higher risks of adverse outcomes at any period of life. Current predictive tools in pregnancy (clinical factors, ultrasound scan, placenta-related biomarkers) fail to identify the true growth-restricted fetus. However, technologies based on metabolomics have generated interesting findings and seem promising. In this systematic review, we will address diagnostic accuracy of metabolomics analyses in predicting FGR.

METHODS AND ANALYSIS

Our primary outcome is small for gestational age infant, as a surrogate for FGR, defined as birth weight below the 10th centile by customised or population-based curves for gestational age. A detailed systematic literature search will be carried in electronic databases and conference abstracts, using the keywords 'fetal growth retardation', 'metabolomics', 'pregnancy' and 'screening' (and their variations). We will include original peer-reviewed articles published from 1998 to 2018, involving pregnancies of fetuses without congenital malformations; sample collection must have been performed before clinical recognition of growth impairment. If additional information is required, authors will be contacted. Reviews, case reports, cross-sectional studies, non-human research and commentaries papers will be excluded. Sample characteristics and the diagnostic accuracy data will be retrieved and analysed. If data allows, we will perform a meta-analysis.

ETHICS AND DISSEMINATION

As this is a systematic review, no ethical approval is necessary. This protocol will be publicised in our institutional websites and results will be submitted for publication in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42018089985.

Determinants of Risk Perception Related to Exposure to Endocrine Disruptors during Pregnancy: A Qualitative and Quantitative Study on French Women

Endocrine disruptors (EDCs) are known as environmental exposure factors. However, they are rarely reported by health professionals in clinical practice, particularly during pregnancy, even though they are associated with many deleterious consequences. The objectives of this study were to estimate the risk perception of pregnant women related to EDC exposure and to evaluate its determinants. A qualitative study based on the Health Belief Model was carried out through interviews of pregnant women and focus group with perinatal, environmental health and prevention professionals in 2015 in the city of Poitiers, France. Then, determinants of risk perception were included in a questionnaire administered to 300 women in the perinatal period through a quantitative study. Scores were subsequently calculated. Perception of EDC risk was defined as perceived severity for different stages of the infant’s development and perceived susceptibility to EDC exposure. The determinants reported in the qualitative study were: age, strong maternal figure, socio-professional category, level of knowledge, and involuntariness of exposure. Age and level of knowledge were confirmed in our statistical model as determinants. Mean score of EDC risk perception was 55.0 ± 18.3 on 100 points. Our study should guide healthcare providers when advising pregnant women about EDC and environmental exposure. Our score for perceived EDC risk and assessment of its known determinants may help to assess the impact and the relevance of prevention programs dedicated to reducing exposure to EDC during pregnancy.

Screening for fetal growth restriction and placental insufficiency

Fetal growth restriction (FGR) continues to be a leading cause of preventable stillbirth and poor neurodevelopmental outcomes in offspring, and furthermore is strongly associated with the obstetrical complications of iatrogenic preterm birth and pre-eclampsia. The terms small for gestational age (SGA) and FGR have, for too long, been considered equivalent and therefore used interchangeably. However, the delivery of improved clinical outcomes requires that clinicians effectively distinguish fetuses that are pathologically growth-restricted from those that are constitutively small. A greater understanding of the multifactorial pathogenesis of both early- and late-onset FGR, especially the role of underlying placental pathologies, may offer insight into targeted treatment strategies that preserve placental function. The new maternal blood biomarker placenta growth factor offers much potential in this context. This review highlights new approaches to effective screening for FGR based on a comprehensive review of: etiology, diagnosis, antenatal surveillance and management. Recent advances in novel imaging methods provide the basis for stepwise multi-parametric testing that may deliver cost-effective screening within existing antenatal care systems.

Metabolomic signatures of low birthweight: Pathways to insulin resistance and oxidative stress

Several studies suggest that low birthweight resulting from restricted intrauterine growth can leave a metabolic footprint which may persist into adulthood. To investigate this, we performed metabolomic profiling on 5036 female twins, aged 18-80, with weight at birth information available from the TwinsUK cohort and performed independent replication in two additional cohorts. Out of 422 compounds tested, 25 metabolites associated with birthweight in these twins, replicated in 1951 men and women from the Hertfordshire Cohort Study (HCS, aged 66) and in 2391 men and women from the North Finland Birth 1986 cohort (NFBC, aged 16). We found distinct heterogeneity between sexes and, after adjusting for multiple tests and heterogeneity, two metabolites were reproducible overall (propionylcarnitine and 3-4-hydroxyphenyllactate). Testing women only, we found other metabolites associated with lower birthweight from the meta-analysis of the three cohorts (2-hydroxy-butyric acid and γ-glutamylleucine). Higher levels of all these metabolites can be linked to insulin resistance, oxidative stress or a dysfunction of energy metabolism, suggesting that low birthweight in both twins and singletons are having an impact on these pathways in adulthood.

Cord Blood Metabolic Signatures of Birth Weight: A Population-Based Study

Birth weight is an important indicator of maternal and fetal health and a predictor of health in later life. However, the determinants of variance in birth weight are still poorly understood. We aimed to identify the biological pathways, which may be perturbed by environmental exposures, that are important in determining birth weight. We applied untargeted mass-spectrometry-based metabolomics to 481 cord blood samples collected at delivery in four birth cohorts from across Europe: ENVIRONAGE (Belgium), INMA (Spain), Piccolipiu (Italy), and Rhea (Greece). We performed a metabolome-wide association scan for birth weight on over 4000 metabolic features, controlling the false discovery rate at 5%. Annotation of compounds was conducted through reference to authentic standards. We identified 68 metabolites significantly associated with birth weight, including vitamin A, progesterone, docosahexaenoic acid, indolelactic acid, and multiple acylcarnitines and phosphatidylcholines. We observed enrichment (p < 0.05) of the tryptophan metabolism, prostaglandin formation, C21-steroid hormone signaling, carnitine shuttle, and glycerophospholipid metabolism pathways. Vitamin A was associated with both maternal smoking and birth weight, suggesting a mediation pathway. Our findings shed new light on the pathways central to fetal growth and will have implications for antenatal and perinatal care and potentially for health in later life.

Biofluid Metabolomics in Preterm Birth Research

This article presents an account of the research carried out so far in the use of metabolomics to find biomarkers of preterm birth (PTB) in fetal, maternal, and newborn biofluids. Metabolomic studies have employed mainly nuclear magnetic resonance spectroscopy or mass spectrometry-based methodologies to analyze, on one hand, prenatal biofluids (amniotic fluid, maternal urine/maternal blood, cervicovaginal fluid) to identify predictive biomarkers of PTB, and on the other hand, biofluids collected at or after birth (amniotic fluid, umbilical cord blood, newborn urine, and newborn blood, maternal blood, or breast milk) to assess and follow up the health status of PTB babies. Besides advancing on the biochemical knowledge of PTB metabolism mainly during the in utero period and at birth, the work carried out has also helped to identify important requirements related to experimental design and analytical protocol that need to be addressed, if translation of these biomarkers to the clinic is to be envisaged. An outlook of possible future developments for the translation of laboratory results to the clinic is presented.

First and second trimester urinary metabolic profiles and fetal growth restriction: an exploratory nested case-control study within the infant development and environment study

BACKGROUND

Routine prenatal care fails to identify a large proportion of women at risk of fetal growth restriction (FGR). Metabolomics, the comprehensive analysis of low molecular weight molecules (metabolites) in biological samples, can provide new and earlier biomarkers of prenatal health. Recent research has suggested possible predictive first trimester urine metabolites correlating to fetal growth restriction in the third trimester. Our objective in this current study was to examine urinary metabolic profiles in the first and second trimester of pregnancy in relation to third trimester FGR in a US population from a large, multi-center cohort study of healthy pregnant women.

METHODS

We conducted a nested case-control study within The Infant Development and the Environment Study (TIDES), a population-based multi-center pregnancy cohort study. We identified 53 cases of FGR based on the AUDIPOG [Neonatal growth - AUDIPOG [Internet]. [cited 29 Nov 2016]. Available from: http://www.audipog.net/courbes_morpho.php?langue=en ] formula for birthweight percentile considering maternal height, age, and prenatal weight, as well as infant sex, gestational age, and birth rank. Cases were matched to 106 controls based on study site, maternal age (± 2 years), parity, and infant sex. NMR spectroscopy was used to assess concentrations of four urinary metabolites that have been previously associated with FGR (tyrosine, acetate, formate, and trimethylamine) in first and second trimester urine samples. We fit multivariate conditional logistic regression models to estimate the odds of FGR in relation to urinary concentrations of these individual metabolites in the first and second trimesters. Exploratory analyses of custom binned spectroscopy results were run to consider other potentially related metabolites.

RESULTS

We found no significant association between the relative concentrations of each of the four metabolites and odds of FGR. Exploratory analyses did not reveal any significant differences in urinary metabolic profiles. Compared with controls, cases delivered earlier (38.6 vs 39.8, p < 0.001), and had lower birthweights (2527 g vs 3471 g, p < 0.001). Maternal BMI was similar between cases and controls.

CONCLUSIONS

First and second trimester concentrations of urinary metabolites (acetate, formate, trimethylamine and tyrosine) did not predict FGR. This inconsistency with previous studies highlights the need for more rigorous investigation and data collection in this area before metabolomics can be clinically applied to obstetrics.

Beyond genomics: understanding exposotypes through metabolomics

BACKGROUND

Over the past 20 years, advances in genomic technology have enabled unparalleled access to the information contained within the human genome. However, the multiple genetic variants associated with various diseases typically account for only a small fraction of the disease risk. This may be due to the multifactorial nature of disease mechanisms, the strong impact of the environment, and the complexity of gene-environment interactions. Metabolomics is the quantification of small molecules produced by metabolic processes within a biological sample. Metabolomics datasets contain a wealth of information that reflect the disease state and are consequent to both genetic variation and environment. Thus, metabolomics is being widely adopted for epidemiologic research to identify disease risk traits. In this review, we discuss the evolution and challenges of metabolomics in epidemiologic research, particularly for assessing environmental exposures and providing insights into gene-environment interactions, and mechanism of biological impact.

MAIN TEXT

Metabolomics can be used to measure the complex global modulating effect that an exposure event has on an individual phenotype. Combining information derived from all levels of protein synthesis and subsequent enzymatic action on metabolite production can reveal the individual exposotype. We discuss some of the methodological and statistical challenges in dealing with this type of high-dimensional data, such as the impact of study design, analytical biases, and biological variance. We show examples of disease risk inference from metabolic traits using metabolome-wide association studies. We also evaluate how these studies may drive precision medicine approaches, and pharmacogenomics, which have up to now been inefficient. Finally, we discuss how to promote transparency and open science to improve reproducibility and credibility in metabolomics.

CONCLUSIONS

Comparison of exposotypes at the human population level may help understanding how environmental exposures affect biology at the systems level to determine cause, effect, and susceptibilities. Juxtaposition and integration of genomics and metabolomics information may offer additional insights. Clinical utility of this information for single individuals and populations has yet to be routinely demonstrated, but hopefully, recent advances to improve the robustness of large-scale metabolomics will facilitate clinical translation.

Translational Systems Pharmacology Studies in Pregnant Women

Pregnancy involves rapid physiological adaptation and complex interplay between mother and fetus. New analytic technologies provide large amounts of genomic, proteomic, and metabolomics data. The integration of these data through bioinformatics, statistical, and systems pharmacology techniques can improve our understanding of the mechanisms of normal maternal physiologic changes and fetal development. New insights into the mechanisms of pregnancy‐related disorders, such as preterm birth (PTB), may lead to the development of new therapeutic interventions and novel biomarkers.

Associations of cord blood metabolites with perinatal characteristics, newborn anthropometry, and cord blood hormones in project viva

CONTEXT

Metabolomics has emerged as a powerful tool to characterize biomarkers and elucidate physiological processes underlying adverse health outcomes. Little is known of these relationships during gestation and infancy, which are critical period for development of metabolic disease risk.

OBJECTIVES

To identify cord blood metabolite patterns associated with birth size; and to investigate relations of the birth size-associated metabolite patterns, and a branched chain amino acid (BCAA) metabolite pattern with a range of newborn and perinatal characteristics.

METHODS

Using untargeted mass-spectrometry, we quantified metabolites in cord blood of 126 mother-child pairs. After excluding 103 xenobiotics, we used principal components analysis (PCA) to consolidate the remaining 606 metabolites into principal components ("factors"). Next, we identified factors associated with gestational age-and sex-standardized birthweight z-score (BW/GA) and examined associations of the BW/GA-associated pattern(s) and the BCAA pattern with cord blood insulin, leptin, adiponectin, insulin-like growth factor (IGF)-1, IGF-2, and IGF binding protein 3 (IGFBP-3) using multivariable linear regression. Finally, we examined associations of maternal/perinatal characteristics with the cord blood metabolite patterns.

RESULTS

Mean BW/GA z-score was 0.27±0.98 units. About half of the infants were male (52.4%) and white (57.1%). Of the 6 factors identified from PCA, one was associated with higher BW/GA: Factor 5, which comprised metabolites involved in energy production (malate, succinate, fumarate) and nucleotide turnover (inosine 5-monophosphate, adenosine 5-monophosphate, cytidine 5-monophosphate) pathways. In multivariable analysis, Factor 5 was related to higher cord blood leptin (1.64 [95% CI: 0.42, 2.87] ng/mL) and IGF-1 even after adjusting for IGFBP-3 (3.35 [0.25, 6.44] ng/mL). The BCAA pattern was associated with higher BW/GA (0.20 [0.03, 0.36] z-scores) and IGFBP-3 (106.5 [44.7, 168.2] ng/mL). No maternal characteristics were associated with either metabolite pattern; however, infants born via Cesarean delivery exhibited a higher score for Factor 5, and gestation length was inversely associated with the BCAA pattern.

CONCLUSIONS

Metabolites in energy production and DNA/RNA turnover pathways in cord blood are associated with larger size at birth, and higher leptin and IGF-1. Similarly, the BCAA pattern was associated with larger birth size and IGFBP-3.

Endocrine Disruptors and Pregnancy: Knowledge, Attitudes and Prevention Behaviors of French Women

Endocrine disrupting chemicals (EDC) are environmental exposure factors that are rarely reported in clinical practice, particularly during pregnancy. This study aimed to describe women's knowledge, attitudes and behaviors towards EDC exposure. A study was conducted in the French Department of Vienne between 2014 and 2016 and comprised semi-structured interviews with pregnant women, a focus group of professionals in perinatology and environmental health, and the administration of a psychosocial questionnaire comprising scores in 300 pregnant or in postpartum period women. The mean score of knowledge was 42.9 ± 9.8 out of 100 (from 13.5 to 75.7). Exposure attitude was determined by risk perception. Mean level of cues to action to reduce their EDC exposure was estimated at 56.9 ± 22.5 out of 100 (from 0 to 100). Anxiety was significantly increased after the questionnaire. Anxiety about EDC was associated with a high score of knowledge (OR = 2.30, 95% CI (1.12-4.71)) and with no pregnancy anxiety (OR = 0.57, 95% CI (0.34-0.95)). Our findings suggest that healthcare providers should consider pregnant women's knowledge and perceptions, possibilities of action, and be careful not to increase their anxiety when advising them about EDC and environmental exposure.