Maternal urinary metabolic signatures of fetal growth and associated clinical and environmental factors in the INMA study

Correlation between newborn weight and serum BCAAs in pregnant women with diabetes

BACKGROUND

Branched-chain amino acids (BCAAs), including leucine, isoleucine, and valine, are essential amino acids for mammals. Maternal BCAAs during pregnancy have been associated with newborn development. Meanwhile, BCAAs have been tightly linked with insulin resistance and diabetes in recent years. Diabetes in pregnancy is a common metabolic disorder. The current study aims to assess the circulating BCAA levels in pregnant women with diabetes and their relationship with neonatal development.

METHODS

The serum concentrations of BCAAs and their corresponding branched-chain α-keto acids (BCKAs) catabolites in 33 pregnant women with normal glucose tolerance, 16 pregnant women with type 2 diabetes before pregnancy (PDGM), and 15 pregnant women with gestational diabetes mellitus (GDM) were determined using a liquid chromatography system coupled to a mass spectrometer. The data were tested for normal distribution and homogeneity of variance before statistical analysis. Correlations were computed with the Pearson correlation coefficient.

RESULTS

The maternal serum BCAAs and BCKAs levels during late pregnancy were higher in women with PGDM than those in healthy women. Meanwhile, the circulating BCAAs and BCKAs showed no significant changes in women with GDM compared with those in healthy pregnant women. Furthermore, the circulating BCAA and BCKA levels in women with PGDM were positively correlated with the weight of the newborn. The circulating leucine level in women with GDM was positively correlated with the weight of the newborn. BCAA and BCKA levels in healthy pregnant women showed no correlation with newborn weight.

CONCLUSIONS

The serum BCAAs in pregnant women with diabetes, which was elevated in PGDM but not GDM, were positively correlated with newborn weight. These findings highlight potential approaches for early identification of high-risk individuals and interventions to reduce the risk of adverse pregnancy outcomes.

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.

Metabolomics to Understand Alterations Induced by Physical Activity during Pregnancy

Physical activity (PA) and exercise have been associated with a reduced risk of cancer, obesity, and diabetes. In the context of pregnancy, maintaining an active lifestyle has been shown to decrease gestational weight gain (GWG) and lower the risk of gestational diabetes mellitus (GDM), hypertension, and macrosomia in offspring. The main pathways activated by PA include BCAAs, lipids, and bile acid metabolism, thereby improving insulin resistance in pregnant individuals. Despite these known benefits, the underlying metabolites and biological mechanisms affected by PA remain poorly understood, highlighting the need for further investigation. Metabolomics, a comprehensive study of metabolite classes, offers valuable insights into the widespread metabolic changes induced by PA. This narrative review focuses on PA metabolomics research using different analytical platforms to analyze pregnant individuals. Existing studies support the hypothesis that exercise behaviour can influence the metabolism of different populations, including pregnant individuals and their offspring. While PA has shown considerable promise in maintaining metabolic health in non-pregnant populations, our comprehension of metabolic changes in the context of a healthy pregnancy remains limited. As a result, further investigation is necessary to clarify the metabolic impact of PA within this unique group, often excluded from physiological research.

Metabolomics insights into the prenatal exposure effects of polybrominated diphenyl ethers on neonatal birth outcomes

BACKGROUND

Effects of polybrominated diphenyl ethers (PBDEs) on neonatal birth outcomes vary across previous studies, and the related mechanism investigation remains poorly understood, especially at the metabolic level.

OBJECTIVES

To evaluate the associations between prenatal PBDEs exposure and neonatal birth outcomes including gestational age, neonatal weight, birth length, head circumference (HC), Apgar score at 1 min (Apgar1) and 5 min, and further reveal the underlying metabolic disorders in a population-based birth cohort study.

METHODS

Gas chromatography-triple quadrupole tandem mass spectrometry (GC-MS/MS) based targeted method and GC-MS based untargeted method were respectively conducted to obtain PBDE levels and metabolic profiles of 200 placental tissue samples from a typical e-waste recycling area (Guiyu) and reference area (Haojiang) in China. Spearman correlation and regression analyses were applied to assess the associations between the placental PBDE levels and birth outcomes. Metabolome-wide association studies and the meet-in-the-middle approach were employed to explore disruptions linking PBDE exposures and the corresponding adverse birth outcomes.

RESULTS

Eight out of 27 PBDE congeners were detected in placenta with more than 50% frequency in at least one district and significantly higher in Guiyu than those in Haojiang. The lower HC and Apgar1 had significant associations with PBDE exposures after adjustment for potential confounders. A total of 66, 16 and 14 metabolites were significantly correlated with PBDE exposures, HC and Apgar1, respectively. 4 and 12 PBDE-related metabolites were significantly associated with the risks of decreasing neonatal HC and Apgar1. The disrupted metabolites were mainly involved in the pentose phosphate pathway, ascorbate metabolism, threonine metabolism, butanoate metabolism, lipid metabolism, and arginine biosynthesis.

CONCLUSIONS

In this birth cohort, higher placental PBDE levels were significantly associated with the lower HC and Apgar1. The associations might be modified by multiple metabolic disturbances through increasing oxidative stress, mediating neurotoxicity, maternal gut microbiota dysbiosis and vasodilatation regulation.

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.

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.

Advancing tools for human early lifecourse exposome research and translation (ATHLETE): Project overview

Early life stages are vulnerable to environmental hazards and present important windows of opportunity for lifelong disease prevention. This makes early life a relevant starting point for exposome studies. The Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project aims to develop a toolbox of exposome tools and a Europe-wide exposome cohort that will be used to systematically quantify the effects of a wide range of community- and individual-level environmental risk factors on mental, cardiometabolic, and respiratory health outcomes and associated biological pathways, longitudinally from early pregnancy through to adolescence. Exposome tool and data development include as follows: (1) a findable, accessible, interoperable, reusable (FAIR) data infrastructure for early life exposome cohort data, including 16 prospective birth cohorts in 11 European countries; (2) targeted and nontargeted approaches to measure a wide range of environmental exposures (urban, chemical, physical, behavioral, social); (3) advanced statistical and toxicological strategies to analyze complex multidimensional exposome data; (4) estimation of associations between the exposome and early organ development, health trajectories, and biological (metagenomic, metabolomic, epigenetic, aging, and stress) pathways; (5) intervention strategies to improve early life urban and chemical exposomes, co-produced with local communities; and (6) child health impacts and associated costs related to the exposome. Data, tools, and results will be assembled in an openly accessible toolbox, which will provide great opportunities for researchers, policymakers, and other stakeholders, beyond the duration of the project. ATHLETE's results will help to better understand and prevent health damage from environmental exposures and their mixtures from the earliest parts of the life course onward.

Analytical challenges in human exposome analysis with focus on environmental analysis combined with metabolomics

Environmental factors, such as chemical exposures, are likely to play a crucial role in the development of several human chronic diseases. However, how the specific exposures contribute to the onset and progress of various diseases is still poorly understood. In part, this is because comprehensive characterization of the chemical exposome is a highly challenging task, both due to its complex dynamic nature as well as due to the analytical challenges. Herein, the analytical challenges in the field of exposome research are reviewed, with specific emphasis on the sampling, sample preparation, and analysis, as well as challenges in the compound identification. The primary focus is on the human chemical exposome, that is, exposures to mixtures of environmental chemicals and its impact on human metabolome. In order to highlight the recent progress in the exposome research in relation to human health and disease, selected examples of human exposome studies are presented.

Global metabolomic profiling reveals hepatic biosignatures that reflect the unique metabolic needs of late-term mother and fetus

OBJECTIVE

Gestational disorders including preeclampsia, growth restriction and diabetes are characterized, in part, by altered metabolic interactions between mother and fetus. Understanding their functional relevance requires metabolic characterization under normotypic conditions.

METHODS

We performed untargeted metabolomics on livers of pregnant, late-term C57Bl/6J mice (N = 9 dams) and their fetuses (pooling 4 fetuses/litter), using UPLC-MS/MS.

RESULTS

Multivariate analysis of 730 hepatic metabolites revealed that maternal and fetal metabolite profiles were highly compartmentalized, and were significantly more similar within fetuses (ρ_average = 0.81), or within dams (ρ_average = 0.79), than within each maternal-fetal dyad (ρ_average = - 0.76), suggesting that fetal hepatic metabolism is under distinct and equally tight metabolic control compared with its respective dam. The metabolite profiles were consistent with known differences in maternal-fetal metabolism. The reduced fetal glucose reflected its limited capacity for gluconeogenesis and dependence upon maternal plasma glucose pools. The fetal decreases in essential amino acids and elevations in their alpha-keto acid carnitine conjugates reflects their importance as secondary fuel sources to meet fetal energy demands. Whereas, contrasting elevations in fetal serine, glycine, aspartate, and glutamate reflects their contributions to endogenous nucleotide synthesis and fetal growth. Finally, the elevated maternal hepatic lipids and glycerol were consistent with a catabolic state that spares glucose to meet competing maternal-fetal energy demands.

CONCLUSIONS

The metabolite profile of the late-term mouse dam and fetus is consistent with prior, non-rodent analyses utilizing plasma and urine. These data position mouse as a suitable model for mechanistic investigation into how maternal-fetal metabolism adapts (or not) to gestational stressors.

Maternal Metabolome in Pregnancy and Childhood Asthma or Recurrent Wheeze in the Vitamin D Antenatal Asthma Reduction Trial

The in utero environment during pregnancy has important implications for the developing health of the child. We aim to examine the potential impact of maternal metabolome at two different timepoints in pregnancy on offspring respiratory health in early life. In 685 mother-child pairs from the Vitamin D Antenatal Asthma Reduction Trial, we assessed the prospective associations between maternal metabolites at both baseline (10–18 weeks gestation) and third trimester (32–38 weeks gestation) and the risk of child asthma or recurrent wheeze by age three using logistic regression models accounting for confounding factors. Subgroup analyses were performed by child sex. Among 632 metabolites, 19 (3.0%) and 62 (9.8%) from baseline and third trimester, respectively, were associated with the outcome (p-value < 0.05). Coffee-related metabolites in the maternal metabolome appeared to be of particular importance. Caffeine, theophylline, trigonelline, quinate, and 3-hydroxypyridine sulfate were inversely associated with asthma risk at a minimum of one timepoint. Additional observations also highlight the roles of steroid and sphingolipid metabolites. Overall, there was a stronger relationship between the metabolome in later pregnancy and offspring asthma risk. Our results suggest that alterations in prenatal metabolites may act as drivers of the development of offspring asthma.

Maternal lipodome across pregnancy is associated with the neonatal DNA methylome

Aim: To classify the association between the maternal lipidome and DNA methylation in cord blood leukocytes. Materials & methods: Untargeted lipidomics was performed on first trimester maternal plasma (M1) and delivery maternal plasma (M3) in 100 mothers from the Michigan Mother-Infant Pairs cohort. Cord blood leukocyte DNA methylation was profiled using the Infinium EPIC bead array and empirical Bayes modeling identified differential DNA methylation related to maternal lipid groups. Results: M3-saturated lysophosphatidylcholine was associated with 45 differentially methylated loci and M3-saturated lysophosphatidylethanolamine was associated with 18 differentially methylated loci. Biological pathways enriched among differentially methylated loci by M3 saturated lysophosphatidylcholines were related to cell proliferation and growth. Conclusion: The maternal lipidome may be influential in establishing the infant epigenome.

Metabolic Signatures of the Exposome-Quantifying the Impact of Exposure to Environmental Chemicals on Human Health

Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point in life. External exposures, such as the “chemical exposome” (exposures to environmental chemicals), affect the host’s metabolism and immune system, which, in turn, mediate the risk of various diseases. Linking such exposures to adverse outcomes, via intermediate phenotypes such as the metabolome, is one of the central themes of exposome research. Much progress has been made in this line of research, including addressing some key challenges such as analytical coverage of the exposome and metabolome, as well as the integration of heterogeneous, multi-omics data. There is strong evidence that chemical exposures have a marked impact on the metabolome, associating with specific disease risks. Herein, we review recent progress in the field of exposome research as related to human health as well as selected metabolic and autoimmune diseases, with specific emphasis on the impacts of chemical exposures on the host metabolome.

Early-life exposure to widespread environmental toxicants and maternal-fetal health risk: A focus on metabolomic biomarkers

Prenatal exposure to widespread environmental toxicants is detrimental to maternal health and fetal development. The effects of environmental toxicants on maternal and fetal metabolic profile changes have not yet been summarized. This systematic review aims to summarize the current studies exploring the association between prenatal exposure to environmental toxicants and metabolic profile alterations in mother and fetus. We searched the MEDLINE (PubMed) electronic database for relevant literature conducted up to September 18, 2019 with some key terms. From the initial 155 articles, 15 articles met the inclusion and exclusion criteria, and consist of highly heterogeneous research methods. Seven studies assessed the effects of multiple environmental pollutants (metals, organic pollutants, nicotine, air pollutants) on the maternal urine and blood metabolomic profile; five studies evaluated the effects of arsenic, polychlorinated biphenyls (PCBs), nicotine, and ambient fine particulate matter (PM_2.5) on the cord blood metabolomic profile; and one study assessed the effects of smoking exposure on the amniotic fluid metabolomic profile. The alteration of metabolic pathways in these studies mainly involve energy metabolism, hormone metabolism, oxidative stress and inflammation. No population study investigated the association between environmental toxicants and placental metabolomics. This systematic review provides evidence that prenatal exposure to a variety of environmental pollutants can affect maternal and fetal metabolomic characteristics. Integration of environmental toxicant exposure and metabolomics data in maternal-fetal samples is helpful to understand the interaction between toxicants and metabolites, so as to reveal the pathogenesis of fetal disease or diseases of fetal origin.

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.

Untargeted Metabolomics Screen of Mid-pregnancy Maternal Serum and Autism in Offspring

Discovering pathophysiologic networks in a blood-based approach may help to generate valuable tools for early treatment or preventive measures in autism. To date targeted or untargeted metabolomics approaches to identify metabolic features and pathways affecting fetal neurodevelopment have rarely been applied to pregnancy samples, that is, an early period potentially relevant for the development of autism spectrum disorders (ASD). We conducted a population-based study relying on autism diagnoses retrieved from California Department of Developmental Services record. After linking cases to and sampling controls from birth certificates, we retrieved stored maternal mid-pregnancy serum samples collected as part of the California Prenatal Screening Program from the California Biobank for children born 2004 to 2010 in the central valley of California. We retrieved serum for 52 mothers whose children developed autism and 62 population controls originally selected from all eligible children matched by birth year and child's sex. Also, we required that these mothers were relatively low or unexposed to air pollution and select pesticides during early pregnancy. We identified differences in metabolite levels in several metabolic pathways, including glycosphingolipid biosynthesis and metabolism, N-glycan and pyrimidine metabolism, bile acid pathways and, importantly, C21-steroid hormone biosynthesis and metabolism. Disturbances in these pathways have been shown to be relevant for neurodevelopment in rare genetic syndromes or implicated in previous studies of autism. This study provides new insight into maternal mid-pregnancy metabolic features possibly related to the development of autism and an incentive to explore whether these pathways and metabolites are useful for early diagnosis, treatment, or prevention. LAY SUMMARY: This study found that in mid-pregnancy the blood of mothers who give birth to a child that develops autism has some characteristic features that are different from those of blood samples taken from control mothers. These features are related to biologic mechanisms that can affect fetal brain development. In the future, these insights may help identify biomarkers for early autism diagnosis and treatment or preventive measures. Autism Res 2020, 13: 1258-1269. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

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.

Analyzing Metabolomics Data for Environmental Health and Exposome Research

The exposome is the cumulative measure of environmental influences and associated biological responses across the life span, with critical relevance for understanding how exposures can impact human health. Metabolomics analysis of biological samples offers unique advantages for examining the exposome. Simultaneous analysis of external exposures, biological responses, and host susceptibility at a systems level can help establish links between external exposures and health outcomes. As metabolomics technologies continue to evolve for the study of the exposome, metabolomics ultimately will help provide valuable insights for exposure risk assessment, and disease prevention and management. Here, we discuss recent advances in metabolomics, and describe data processing protocols that can enable analysis of the exposome. This chapter focuses on using liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics for analysis of the exposome, including (1) preprocessing of untargeted metabolomics data, (2) identification of exposure chemicals and their metabolites, and (3) methods to establish associations between exposures and diseases.

Systematic Isolation and Structure Elucidation of Urinary Metabolites Optimized for the Analytical-Scale Molecular Profiling Laboratory

Annotation and identification of metabolite biomarkers is critical for their biological interpretation in metabolic phenotyping studies, presenting a significant bottleneck in the successful implementation of untargeted metabolomics. Here, a systematic multistep protocol was developed for the purification and de novo structural elucidation of urinary metabolites. The protocol is most suited for instances where structure elucidation and metabolite annotation are critical for the downstream biological interpretation of metabolic phenotyping studies. First, a bulk urine pool was desalted using ion-exchange resins enabling large-scale fractionation using precise iterations of analytical scale chromatography. Primary urine fractions were collected and assembled into a “fraction bank” suitable for long-term laboratory storage. Secondary and tertiary fractionations exploited differences in selectivity across a range of reversed-phase chemistries, achieving the purification of metabolites of interest yielding an amount of material suitable for chemical characterization. To exemplify the application of the systematic workflow in a diverse set of cases, four metabolites with a range of physicochemical properties were selected and purified from urine and subjected to chemical formula and structure elucidation by respective magnetic resonance mass spectrometry (MRMS) and NMR analyses. Their structures were fully assigned as tetrahydropentoxyline, indole-3-acetic-acid-O-glucuronide, p-cresol glucuronide, and pregnanediol-3-glucuronide. Unused effluent was collected, dried, and returned to the fraction bank, demonstrating the viability of the system for repeat use in metabolite annotation with a high degree of efficiency.

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.

Urine Nuclear Magnetic Resonance (NMR) Metabolomics in Age-Related Macular Degeneration

Biofluid biomarkers of age-related macular degeneration (AMD) are still lacking, and their identification is challenging. Metabolomics is well-suited to address this need, and urine is a valuable accessible biofluid. This study aimed to characterize the urinary metabolomic signatures of patients with different stages of AMD and a control group (>50 years). It was a prospective, cross-sectional study, where subjects from two cohorts were included: 305 from Coimbra, Portugal (AMD patients n = 252; controls n = 53) and 194 from Boston, United States (AMD patients n = 147; controls n = 47). For all participants, we obtained color fundus photographs (for AMD staging) and fasting urine samples, which were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy. Our results revealed that in both cohorts, urinary metabolomic profiles differed mostly between controls and late AMD patients, but important differences were also found between controls and subjects with early AMD. Analysis of the metabolites responsible for these separations revealed that, even though distinct features were observed for each cohort, AMD was in general associated with depletion of excreted citrate and selected amino acids at some stage of the disease, suggesting enhanced energy requirements. In conclusion, NMR metabolomics enabled the identification of urinary signals of AMD and its severity stages, which might represent potential metabolomic biomarkers of the disease.

Maternal metabolites during pregnancy are associated with newborn outcomes and hyperinsulinaemia across ancestries

AIMS/HYPOTHESIS

We aimed to determine the association of maternal metabolites with newborn adiposity and hyperinsulinaemia in a multi-ethnic cohort of mother-newborn dyads.

METHODS

Targeted and non-targeted metabolomics assays were performed on fasting and 1 h serum samples from a total of 1600 mothers in four ancestry groups (Northern European, Afro-Caribbean, Mexican American and Thai) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, underwent an OGTT at ~28 weeks gestation and whose newborns had anthropometric measurements at birth.

RESULTS

In this observational study, meta-analyses demonstrated significant associations of maternal fasting and 1 h metabolites with birthweight, cord C-peptide and/or sum of skinfolds across ancestry groups. In particular, maternal fasting triacylglycerols were associated with newborn sum of skinfolds. At 1 h, several amino acids, fatty acids and lipid metabolites were associated with one or more newborn outcomes. Network analyses revealed clusters of fasting acylcarnitines, amino acids, lipids and fatty acid metabolites associated with cord C-peptide and sum of skinfolds, with the addition of branched-chain and aromatic amino acids at 1 h.

CONCLUSIONS/INTERPRETATION

The maternal metabolome during pregnancy is associated with newborn outcomes. Maternal levels of amino acids, acylcarnitines, lipids and fatty acids and their metabolites during pregnancy relate to fetal growth, adiposity and cord C-peptide, independent of maternal BMI and blood glucose levels.

Multiple elements related to metabolic markers in the context of gestational diabetes mellitus in meconium

BACKGROUND

Gestational diabetes mellitus (GDM) is a typical fetus development niches dysfunction and many toxic/nutrient elements have been associated with its onset and progression. However, the classic epidemiologic approach is regarded as "black-box epidemiology" and fails to elucidate these elements' biological roles on the damaged fetus developmental microenvironment.

OBJECTIVE

We aimed to characterize the associations between meconium of multiple elements with GDM for illustrating their interruption effects on in-uterus microenvironment.

METHODS

In this case-control study (n = 137 cases; n = 197 controls), the participants were nested from a cross-sectional retrospection of 1359 recruitments in Xiamen, China. Twenty-one meconium elements were characterized using inductively coupled plasma mass spectrometry (ICP-MS) or inductively coupled plasma optical emission spectrometry (ICP-OES). For shifting the present paradigm from a black-box approach to a molecular approach, GDM-related metabolic markers were identified in our previous metabolome report. Based on the meet-in-middle strategy, the associations among the elements, metabolic markers and GDM incidence were assessed by using redundancy analysis and correlation-adjusted correlation; mediation analysis was further used to test the hypothesis that metabolic markers mediate the associations of the elements with GDM incidence.

RESULTS

Eight elements were related with the GDM occurrence in dose-dependent manners, which positively (Al, As, Ba, Cd, Hg, and Sn) or negatively (Ca and V) associated with GDM. Among them, As, Cd, Ba, and Ca significantly contributed to the variation of GDM-related metabolic markers. Additionally, the associations of Cd, Ba, Ca and As with GDM were mediated by the metabolic markers which majorly involved in the lipid metabolism and the Adenosine/l-Arginine/Nitric Oxide (ALANO) pathways.

CONCLUSIONS

The two-side mediations of meconium metabolic markers between the multiple elements and GDM occurrence indicated that maternal exposure to As, Ba, Cd, and Ca may be associated with the dysfunction of fetus development niche through disrupting lipid metabolism and ALANO pathways.

Urine Metabolic Signatures of Multiple Environmental Pollutants in Pregnant Women: An Exposome Approach

Exposure to environmental pollutants, particularly during pregnancy, can have adverse consequences on child development but little is known about the effects of pollutant mixtures on endogenous metabolism in pregnant women. We aimed to identify urinary metabolic signatures associated with low level exposure to multiple environmental pollutants in pregnant women from the INMA (INfancia y Medio Ambiente) birth cohort (Spain, N = 750). 35 chemical exposures were quantified in first trimester blood samples (organochlorine pesticides, PCBs, PFAS), in cord blood (mercury), and twice in urine at 12 and 32 weeks of pregnancy (metals, phthalates, bisphenol A). ¹H nuclear magnetic resonance (NMR) metabolic profiles of urine were acquired in the same samples as pollutants. We explored associations between exposures and metabolism through an exposome-metabolome wide association scan and multivariate O2PLS modeling. Novel and reproducible associations were found across two periods of pregnancy for three nonpersistent pollutants and across two subcohorts for four of the persistent pollutants. We found novel metabolic signatures associated with arsenic exposure: TMAO and dimethylamine possibly related to gut microbial methylamine metabolism and homarine related to fish intake. Tobacco smoke exposure was related to coffee metabolism and PCBs with 3-hydroxyvaleric acid, usually released under ketoacidosis. These findings will have implications for further understanding of maternal-fetal health, and health across the life-course.

Determinants of the urinary and serum metabolome in children from six European populations

BACKGROUND

Environment and diet in early life can affect development and health throughout the life course. Metabolic phenotyping of urine and serum represents a complementary systems-wide approach to elucidate environment-health interactions. However, large-scale metabolome studies in children combining analyses of these biological fluids are lacking. Here, we sought to characterise the major determinants of the child metabolome and to define metabolite associations with age, sex, BMI and dietary habits in European children, by exploiting a unique biobank established as part of the Human Early-Life Exposome project ( http://www.projecthelix.eu ).

METHODS

Metabolic phenotypes of matched urine and serum samples from 1192 children (aged 6-11) recruited from birth cohorts in six European countries were measured using high-throughput ¹H nuclear magnetic resonance (NMR) spectroscopy and a targeted LC-MS/MS metabolomic assay (Biocrates AbsoluteIDQ p180 kit).

RESULTS

We identified both urinary and serum creatinine to be positively associated with age. Metabolic associations to BMI z-score included a novel association with urinary 4-deoxyerythreonic acid in addition to valine, serum carnitine, short-chain acylcarnitines (C3, C5), glutamate, BCAAs, lysophosphatidylcholines (lysoPC a C14:0, lysoPC a C16:1, lysoPC a C18:1, lysoPC a C18:2) and sphingolipids (SM C16:0, SM C16:1, SM C18:1). Dietary-metabolite associations included urinary creatine and serum phosphatidylcholines (4) with meat intake, serum phosphatidylcholines (12) with fish, urinary hippurate with vegetables, and urinary proline betaine and hippurate with fruit intake. Population-specific variance (age, sex, BMI, ethnicity, dietary and country of origin) was better captured in the serum than in the urine profile; these factors explained a median of 9.0% variance amongst serum metabolites versus a median of 5.1% amongst urinary metabolites. Metabolic pathway correlations were identified, and concentrations of corresponding metabolites were significantly correlated (r > 0.18) between urine and serum.

CONCLUSIONS

We have established a pan-European reference metabolome for urine and serum of healthy children and gathered critical resources not previously available for future investigations into the influence of the metabolome on child health. The six European cohort populations studied share common metabolic associations with age, sex, BMI z-score and main dietary habits. Furthermore, we have identified a novel metabolic association between threonine catabolism and BMI of children.

First-trimester metabolomic prediction of stillbirth

Background: Stillbirth remains a major problem in both developing and developed countries. Omics evaluation of stillbirth has been highlighted as a top research priority. Objective: To identify new putative first-trimester biomarkers in maternal serum for stillbirth prediction using metabolomics-based approach. Methods: Targeted, nuclear magnetic resonance (NMR) and mass spectrometry (MS), and untargeted liquid chromatography-MS (LC-MS) metabolomic analyses were performed on first-trimester maternal serum obtained from 60 cases that subsequently had a stillbirth and 120 matched controls. Metabolites by themselves or in combination with clinical factors were used to develop logistic regression models for stillbirth prediction. Prediction of stillbirths overall, early (<28 weeks and <32 weeks), those related to growth restriction/placental disorder, and unexplained stillbirths were evaluated. Results: Targeted metabolites including glycine, acetic acid, L-carnitine, creatine, lysoPCaC18:1, PCaeC34:3, and PCaeC44:4 predicted stillbirth overall with an area under the curve [AUC, 95% confidence interval (CI)] = 0.707 (0.628-0.785). When combined with clinical predictors the AUC value increased to 0.740 (0.667-0.812). First-trimester targeted metabolites also significantly predicted early, unexplained, and placental-related stillbirths. Untargeted LC-MS features combined with other clinical predictors achieved an AUC (95%CI) = 0.860 (0.793-0.927) for the prediction of stillbirths overall. We found novel preliminary evidence that, verruculotoxin, a toxin produced by common household molds, might be linked to stillbirth. Conclusions: We have identified novel biomarkers for stillbirth using metabolomics and demonstrated the feasibility of first-trimester prediction.

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.

Preliminary metabolomics analysis of placenta in maternal obesity

INTRODUCTION

Metabolomics identifies phenotypical groups with specific metabolic profiles, being increasingly applied to several pregnancy conditions. This is the first preliminary study analyzing placental metabolomics in normal weight (NW) and obese (OB) pregnancies.

METHODS

Twenty NW (18.5 ≤ BMI< 25 kg/m²) and eighteen OB (BMI≥ 30 kg/m²) pregnancies were studied. Placental biopsies were collected at elective caesarean section. Metabolites extraction method was optimized for hydrophilic and lipophilic phases, then analyzed with GC-MS. Univariate and PLS-DA multivariate analysis were applied.

RESULTS

Univariate analysis showed increased uracil levels while multivariate PLS-DA analysis revealed lower levels of LC-PUFA derivatives in the lipophilic phase and several metabolites with significantly different levels in the hydrophilic phase of OB vs NW.

DISCUSSION

Placental metabolome analysis of obese pregnancies showed differences in metabolites involved in antioxidant defenses, nucleotide production, as well as lipid synthesis and energy production, supporting a shift towards higher placental metabolism. OB placentas also showed a specific fatty acids profile suggesting a disruption of LC-PUFA biomagnification. This study can lay the foundation to further metabolomic placental characterization in maternal obesity. Metabolic signatures in obese placentas may reflect changes occurring in the intrauterine metabolic environment, which may affect the development of adult diseases.

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.

Targeted Metabolomics Demonstrates Distinct and Overlapping Maternal Metabolites Associated With BMI, Glucose, and Insulin Sensitivity During Pregnancy Across Four Ancestry Groups

OBJECTIVE

We used targeted metabolomics in pregnant mothers to compare maternal metabolite associations with maternal BMI, glycemia, and insulin sensitivity.

RESEARCH DESIGN AND METHODS

Targeted metabolomic assays of clinical metabolites, amino acids, and acylcarnitines were performed on fasting and 1-h postglucose serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American mothers (400 from each ancestry group) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and underwent an oral glucose tolerance test at ∼28 weeks gestation.

RESULTS

K-means clustering, which identified patterns of metabolite levels across ancestry groups, demonstrated that, at both fasting and 1-h, levels of the majority of metabolites were similar across ancestry groups. Meta-analyses demonstrated association of a broad array of fasting and 1-h metabolites, including lipids and amino acids and their metabolites, with maternal BMI, glucose levels, and insulin sensitivity before and after adjustment for the different phenotypes. At fasting and 1 h, a mix of metabolites was identified that were common across phenotypes or associated with only one or two phenotypes. Partial correlation estimates, which allowed comparison of the strength of association of different metabolites with maternal phenotypes, demonstrated that metabolites most strongly associated with different phenotypes included some that were common across as well as unique to each phenotype.

CONCLUSIONS

Maternal BMI and glycemia have metabolic signatures that are both shared and unique to each phenotype. These signatures largely remain consistent across different ancestry groups and may contribute to the common and independent effects of these two phenotypes on adverse pregnancy outcomes.

Univariate predictors of maternal concentrations of environmental chemicals: The MIREC study

BACKGROUND

The developing fetus and pregnant woman can be exposed to a variety of environmental chemicals that may adversely affect their health. Moreover, environmental exposure and risk disparities are associated with different social determinants, including socioeconomic status (SES) and demographic indicators. Our aim was to investigate whether and how maternal concentrations of a large panel of persistent and non-persistent environmental chemicals vary according to sociodemographic and lifestyle characteristics in a large pregnancy and birth cohort.

METHODS

Data were analyzed from the Maternal-Infant Research on Environmental Chemicals (MIREC) Study, a cohort of pregnant women (N=2001) recruited over four years (2008-2011) in 10 cities across Canada. In all, 1890 urine and 1938 blood samples from the first trimester (1st and 3rd trimester for metals) were analysed and six sociodemographic and lifestyle indicators were assessed: maternal age, household income, parity, smoking status, country of birth and pre-pregnancy body mass index (BMI).

RESULTS

We found these indicators to be significantly associated with many of the chemicals measured in maternal blood and urine. Women born outside Canada had significantly higher concentrations of di-2-ethylhexyl and diethyl phthalate metabolites, higher levels of all metals except cadmium (Cd), as well as higher levels of polychlorinated biphenyls (PCBs) and legacy organochlorine pesticides (OCPs). Nulliparity was associated with higher concentrations of dialkyl phosphates (DAPs), arsenic, dimethylarsinic acid (DMAA), perfluoroalkyl substances (PFASs) and many of the persistent organic pollutants. Smokers had higher levels of bisphenol A, Cd and perfluorohexane sulfonate, while those women who had never smoked had higher levels of triclosan, DMAA, manganese and some OCPs.

CONCLUSION

Our results demonstrated that inequitable distribution of exposure to chemicals among populations within a country can occur. Sociodemographic and lifestyle factors are an important component of a thorough risk assessment as they can impact the degree of exposure and may modify the individual's susceptibility to potential health effects due to differences in lifestyle, cultural diets, and aging.