Metabolomics in the developmental origins of obesity and its cardiometabolic consequences

Identification of the serum metabolites associated with cow milk consumption in Chinese Peri-/Postmenopausal women

Cow milk consumption (CMC) and downstream alterations of serum metabolites are commonly considered important factors regulating human health status. Foods may lead to metabolic changes directly or indirectly through remodelling gut microbiota (GM). We sought to identify the metabolic alterations in Chinese Peri-/Postmenopausal women with habitual CMC and explore if the GM mediates the CMC-metabolite associations. 346 Chinese Peri-/Postmenopausal women participants were recruited in this study. Fixed effects regression and partial least squares discriminant analysis (PLS-DA) were applied to reveal alterations of serum metabolic features in different CMC groups. Spearman correlation coefficient was computed to detect metabolome-metagenome association. 36 CMC-associated metabolites including palmitic acid (FA(16:0)), 7alpha-hydroxy-4-cholesterin-3-one (7alphaC4), citrulline were identified by both fixed effects regression (FDR < 0.05) and PLS-DA (VIP score > 2). Some significant metabolite-GM associations were observed, including FA(16:0) with gut species Bacteroides ovatus, Bacteroides sp.D2. These findings would further prompt our understanding of the effect of cow milk on human health.

Longitudinal associations of an exposome score with serum metabolites from childhood to adolescence

Environmental and lifestyle factors, including air pollution, impaired diet, and low physical activity, have been associated with cardiometabolic risk factors in childhood and adolescence. However, environmental and lifestyle exposures do not exert their physiological effects in isolation. This study investigated associations between an exposome score to measure the impact of multiple exposures, including diet, physical activity, sleep duration, air pollution, and socioeconomic status, and serum metabolites measured using LC-MS and NMR, compared to the individual components of the score. A general population of 504 children aged 6-9 years at baseline was followed up for eight years. Data were analysed with linear mixed-effects models using the R software. The exposome score was associated with 31 metabolites, of which 12 metabolites were not associated with any individual exposure category. These findings highlight the value of a composite score to predict metabolic changes associated with multiple environmental and lifestyle exposures since childhood.

Maternal Serum Metabolomics in Mid-Pregnancy Identifies Lipid Pathways as a Key Link to Offspring Obesity in Early Childhood

Maternal metabolism during pregnancy shapes offspring health via in utero programming. In the Healthy Start study, we identified five subgroups of pregnant women based on conventional metabolic biomarkers: Reference (n = 360); High HDL-C (n = 289); Dyslipidemic-High TG (n = 149); Dyslipidemic-High FFA (n = 180); Insulin Resistant (IR)-Hyperglycemic (n = 87). These subgroups not only captured metabolic heterogeneity among pregnant participants but were also associated with offspring obesity in early childhood, even among women without obesity or diabetes. Here, we utilize metabolomics data to enrich characterization of the metabolic subgroups and identify key compounds driving between-group differences. We analyzed fasting blood samples from 1065 pregnant women at 18 gestational weeks using untargeted metabolomics. We used weighted gene correlation network analysis (WGCNA) to derive a global network based on the Reference subgroup and characterized distinct metabolite modules representative of the different metabolomic profiles. We used the mummichog algorithm for pathway enrichment and identified key compounds that differed across the subgroups. Eight metabolite modules representing pathways such as the carnitine-acylcarnitine translocase system, fatty acid biosynthesis and activation, and glycerophospholipid metabolism were identified. A module that included 189 compounds related to DHA peroxidation, oxidative stress, and sex hormone biosynthesis was elevated in the Insulin Resistant-Hyperglycemic vs. the Reference subgroup. This module was positively correlated with total cholesterol (R:0.10; p-value < 0.0001) and free fatty acids (R:0.07; p-value < 0.05). Oxidative stress and inflammatory pathways may underlie insulin resistance during pregnancy, even below clinical diabetes thresholds. These findings highlight potential therapeutic targets and strategies for pregnancy risk stratification and reveal mechanisms underlying the developmental origins of metabolic disease risk.

The influence of maternal prepregnancy weight and gestational weight gain on the umbilical cord blood metabolome: a case-control study

BACKGROUND

Maternal overweight/obesity and excessive gestational weight gain (GWG) are frequently reported to be risk factors for obesity and other metabolic disorders in offspring. Cord blood metabolites provide information on fetal nutritional and metabolic health and could provide an early window of detection of potential health issues among newborns. The aim of the study was to explore the impact of maternal prepregnancy overweight/obesity and excessive GWG on cord blood metabolic profiles.

METHODS

A case control study including 33 pairs of mothers with prepregnancy overweight/obesity and their neonates, 30 pairs of mothers with excessive GWG and their neonates, and 32 control mother-neonate pairs. Untargeted metabolomic profiling of umbilical cord blood samples were performed using UHPLC‒MS/MS.

RESULTS

Forty-six metabolites exhibited a significant increase and 60 metabolites exhibited a significant reduction in umbilical cord blood from overweight and obese mothers compared with mothers with normal body weight. Steroid hormone biosynthesis and neuroactive ligand‒receptor interactions were the two top-ranking pathways enriched with these metabolites (P = 0.01 and 0.03, respectively). Compared with mothers with normal GWG, in mothers with excessive GWG, the levels of 63 metabolites were increased and those of 46 metabolites were decreased in umbilical cord blood. Biosynthesis of unsaturated fatty acids was the most altered pathway enriched with these metabolites (P < 0.01).

CONCLUSIONS

Prepregnancy overweight and obesity affected the fetal steroid hormone biosynthesis pathway, while excessive GWG affected fetal fatty acid metabolism. This emphasizes the importance of preconception weight loss and maintaining an appropriate GWG, which are beneficial for the long-term metabolic health of offspring.

Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity

Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.

Integrative multiomics analysis of infant gut microbiome and serum metabolome reveals key molecular biomarkers of early onset childhood obesity

Evidence supports a complex interplay of gut microbiome and host metabolism as regulators of obesity. The metabolic phenotype and microbial metabolism of host diet may also contribute to greater obesity risk in children early in life. This study aimed to identify features that discriminated overweight/obese from normal weight infants by integrating gut microbiome and serum metabolome profiles. This prospective analysis included 50 South Asian children living in Canada, selected from the SouTh Asian biRth cohorT (START). Serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry and the relative abundance of bacterial 16S rRNA gene amplicon sequence variant was evaluated at 1 year. Cumulative body mass index (BMI_AUC) and skinfold thickness (SSF_AUC) scores were calculated from birth to 3 years as the total area under the growth curve (AUC). BMI_AUC and/or SSF_AUC >85th percentile was used to define overweight/obesity. Data Integration Analysis for Biomarker discovery using Latent cOmponent (DIABLO) was used to identify discriminant features associated with childhood overweight/obesity. The associations between identified features and anthropometric measures were examined using logistic regression. Circulating metabolites including glutamic acid, acetylcarnitine, carnitine, and threonine were positively, whereas γ-aminobutyric acid (GABA), symmetric dimethylarginine (SDMA), and asymmetric dimethylarginine (ADMA) were negatively associated with childhood overweight/obesity. The abundance of the Pseudobutyrivibrio and Lactobacillus genera were positively, and Clostridium sensu stricto 1 and Akkermansia were negatively associated with childhood overweight/obesity. Integrative analysis revealed that Akkermansia was positively whereas Lactobacillus was inversely correlated with GABA and SDMA, and Pseudobutyrivibrio was inversely correlated with GABA. This study provides insights into metabolic and microbial signatures which may regulate satiety, energy metabolism, inflammatory processes, and/or gut barrier function, and therefore, obesity trajectories in childhood. Understanding the functional capacity of these molecular features and potentially modifiable risk factors such as dietary exposures early in life may offer a novel approach for preventing childhood obesity.

Childhood Obesity and the Cryptic Language of the Microbiota: Metabolomics’ Upgrading

The growing obesity epidemic in childhood is increasingly concerning for the related physical and psychological consequences, with a significant impact on health care costs in both the short and the long term. Nonetheless, the scientific community has not yet completely clarified the complex metabolic mechanisms underlying body weight alterations. In only a small percentage of cases, obesity is the result of endocrine, monogenic, or syndromic causes, while in much more cases, lifestyle plays a crucial role in obesity development. In this context, the pediatric age appears to be of considerable importance as prevention strategies together with early intervention can represent important therapeutic tools not only to counteract the comorbidities that increasingly affect children but also to hinder the persistence of obesity in adulthood. Although evidence in the literature supporting the alteration of the microbiota as a critical factor in the etiology of obesity is abundant, it is not yet fully defined and understood. However, increasingly clear evidence is emerging regarding the existence of differentiated metabolic profiles in obese children, with characteristic metabolites. The identification of specific pathology-related biomarkers and the elucidation of the altered metabolic pathways would therefore be desirable in order to clarify aspects that are still poorly understood, such as the consequences of the interaction between the host, the diet, and the microbiota. In fact, metabolomics can characterize the biological behavior of a specific individual in response to external stimuli, offering not only an eventual effective screening and prevention strategy but also the possibility of evaluating adherence and response to dietary intervention.

Predictive Metabolomic Markers in Early to Mid-pregnancy for Gestational Diabetes Mellitus: A Prospective Test and Validation Study

Gestational diabetes mellitus (GDM) predisposes pregnant individuals to perinatal complications and long-term diabetes and cardiovascular diseases. We developed and validated metabolomic markers for GDM in a prospective test-validation study. In a case-control sample within the PETALS cohort (GDM n = 91 and non-GDM n = 180; discovery set), a random PETALS subsample (GDM n = 42 and non-GDM n = 372; validation set 1), and a case-control sample within the GLOW trial (GDM n = 35 and non-GDM n = 70; validation set 2), fasting serum untargeted metabolomics were measured by gas chromatography/time-of-flight mass spectrometry. Multivariate enrichment analysis examined associations between metabolites and GDM. Ten-fold cross-validated LASSO regression identified predictive metabolomic markers at gestational weeks (GW) 10-13 and 16-19 for GDM. Purinone metabolites at GW 10-13 and 16-19 and amino acids, amino alcohols, hexoses, indoles, and pyrimidine metabolites at GW 16-19 were positively associated with GDM risk (false discovery rate <0.05). A 17-metabolite panel at GW 10-13 outperformed the model using conventional risk factors, including fasting glycemia (area under the curve: discovery 0.871 vs. 0.742, validation 1 0.869 vs. 0.731, and validation 2 0.972 vs. 0.742; P < 0.01). Similar results were observed with a 13-metabolite panel at GW 17-19. Dysmetabolism is present early in pregnancy among individuals progressing to GDM. Multimetabolite panels in early pregnancy can predict GDM risk beyond conventional risk factors.

Rodents on a high-fat diet born to mothers with gestational diabetes exhibit sex-specific lipidomic changes in reproductive organs

Maternal gestatonal diabetes mellitus (GDM) and offspring high-fat diet (HFD) have been shown to have sex-specific detrimental effects on the health of the offspring. Maternal GDM combined with an offspring HFD alters the lipidomic profiles of offspring reproductive organs with sex hormones and increases insulin signaling, resulting in offspring obesity and diabetes. The pre-pregnancy maternal GDM mice model is established by feeding maternal C57BL/6 mice and their offspring are fed with either a HFD or a low-fat diet (LFD). Testis, ovary and liver are collected from offspring at 20 weeks of age. The lipidomic profiles of the testis and ovary are characterized using gas chromatography-mass spectrometry. Male offspring following a HFD have elevated body weight. In reproductive organs and hormones, male offspring from GDM mothers have decreased testes weights and testosterone levels, while female offspring from GDM mothers show increased ovary weights and estrogen levels. Maternal GDM aggravates the effects of an offspring HFD in male offspring on the AKT pathway, while increasing the risk of developing inflammation when expose to a HFD in female offspring liver. Testes are prone to the effect of maternal GDM, whereas ovarian metabolite profiles are upregulated in maternal GDM and downregulated in offspring following an HFD. Maternal GDM and an offspring HFD have different metabolic effects on offspring reproductive organs, and PUFAs may protect against detrimental outcomes in the offspring, such as obesity and diabetes.

Metabolomic Predictors of Dysglycemia in Two U.S. Youth Cohorts

Here, we seek to identify metabolite predictors of dysglycemia in youth. In the discovery analysis among 391 youth in the Exploring Perinatal Outcomes among CHildren (EPOCH) cohort, we used reduced rank regression (RRR) to identify sex-specific metabolite predictors of impaired fasting glucose (IFG) and elevated fasting glucose (EFG: Q4 vs. Q1 fasting glucose) 6 years later and compared the predictive capacity of four models: Model 1: ethnicity, parental diabetes, in utero exposure to diabetes, and body mass index (BMI); Model 2: Model 1 covariates + baseline waist circumference, insulin, lipids, and Tanner stage; Model 3: Model 2 + baseline fasting glucose; Model 4: Model 3 + baseline metabolite concentrations. RRR identified 19 metabolite predictors of fasting glucose in boys and 14 metabolite predictors in girls. Most compounds were on lipid, amino acid, and carbohydrate metabolism pathways. In boys, no improvement in aurea under the receiver operating characteristics curve AUC occurred until the inclusion of metabolites in Model 4, which increased the AUC for prediction of IFG (7.1%) from 0.81 to 0.97 (p = 0.002). In girls, %IFG was too low for regression analysis (3.1%), but we found similar results for EFG. We replicated the results among 265 youth in the Project Viva cohort, focusing on EFG due to low %IFG, suggesting that the metabolite profiles identified herein have the potential to improve the prediction of glycemia in youth.

Non-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping review

OBJECTIVE

To summarize the application of non-targeted metabolomics in epidemiological studies that assessed metabolite and metabolic pathway alterations associated with per- and polyfluoroalkyl substances (PFAS) exposure.

RECENT FINDINGS

Eleven human studies published before April 1st, 2021 were identified through database searches (PubMed, Dimensions, Web of Science Core Collection, Embase, Scopus), and citation chaining (Citationchaser). The sample sizes of these studies ranged from 40 to 965, involving children and adolescents (n = 3), non-pregnant adults (n = 5), or pregnant women (n = 3). High-resolution liquid chromatography-mass spectrometry was the primary analytical platform to measure both PFAS and metabolome. PFAS were measured in either plasma (n = 6) or serum (n = 5), while metabolomic profiles were assessed using plasma (n = 6), serum (n = 4), or urine (n = 1). Four types of PFAS (perfluorooctane sulfonate(n = 11), perfluorooctanoic acid (n = 10), perfluorohexane sulfonate (n = 9), perfluorononanoic acid (n = 5)) and PFAS mixtures (n = 7) were the most studied. We found that alterations to tryptophan metabolism and the urea cycle were most reported PFAS-associated metabolomic signatures. Numerous lipid metabolites were also suggested to be associated with PFAS exposure, especially key metabolites in glycerophospholipid metabolism which is critical for biological membrane functions, and fatty acids and carnitines which are relevant to the energy supply pathway of fatty acid oxidation. Other important metabolome changes reported included the tricarboxylic acid (TCA) cycle regarding energy generation, and purine and pyrimidine metabolism in cellular energy systems.

CONCLUSIONS

There is growing interest in using non-targeted metabolomics to study the human physiological changes associated with PFAS exposure. Multiple PFAS were reported to be associated with alterations in amino acid and lipid metabolism, but these results are driven by one predominant type of pathway analysis thus require further confirmation. Standardizing research methods and reporting are recommended to facilitate result comparison. Future studies should consider potential differences in study methodology, use of prospective design, and influence from confounding bias and measurement errors.

Metabolomic Profiles in Childhood and Adolescence Are Associated with Fetal Overnutrition

Fetal overnutrition predisposes offspring to increased metabolic risk. The current study used metabolomics to assess sustained differences in serum metabolites across childhood and adolescence among youth exposed to three typologies of fetal overnutrition: maternal obesity only, gestational diabetes mellitus (GDM) only, and obesity + GDM. We included youth exposed in utero to obesity only (BMI ≥ 30; n = 66), GDM only (n = 56), obesity + GDM (n = 25), or unexposed (n = 297), with untargeted metabolomics measured at ages 10 and 16 years. We used linear mixed models to identify metabolites across both time-points associated with exposure to any overnutrition, using a false-discovery-rate correction (FDR) <0.20. These metabolites were included in a principal component analysis (PCA) to generate profiles and assess metabolite profile differences with respect to overnutrition typology (adjusted for prenatal smoking, offspring age, sex, and race/ethnicity). Fetal overnutrition was associated with 52 metabolites. PCA yielded four factors accounting for 17−27% of the variance, depending on age of measurement. We observed differences in three factor patterns with respect to overnutrition typology: sphingomyelin-mannose (8−13% variance), skeletal muscle metabolism (6−10% variance), and 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF; 3−4% variance). The sphingomyelin-mannose factor score was higher among offspring exposed to obesity vs. GDM. Exposure to obesity + GDM (vs. GDM or obesity only) was associated with higher skeletal muscle metabolism and CMPF scores. Fetal overnutrition is associated with metabolic changes in the offspring, but differences between typologies of overnutrition account for a small amount of variation in the metabolome, suggesting there is likely greater pathophysiological overlap than difference.

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.

Study on toxicity effects of environmental pollutants based on metabolomics: A review

In the past few decades, the toxic effects of environmental pollutants on non-target organisms have received more and more attention. As a new omics technology, metabolomics can clarify the metabolic homeostasis of the organism at the overall level by studying the changes in the relative contents of endogenous metabolites in the organism. Recently, a large number of studies have used metabolomics technology to study the toxic effects of environmental pollutants on organisms. In this review, we reviewed the analysis processes and data processes of metabolomics and its application in the study of the toxic effects of environmental pollutants including heavy metals, pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, polybrominated diphenyl ethers and microplastics. In addition, we emphasized that the combination of metabolomics and other omics technologies will help to explore the toxic mechanism of environmental pollutants and provide new research ideas for the toxicological evaluation of environmental pollutants.

Associations of maternal bisphenol urine concentrations during pregnancy with neonatal metabolomic profiles

BACKGROUND

Fetal exposure to bisphenols is associated with altered fetal growth, adverse birth outcomes and childhood cardio-metabolic risk factors. Metabolomics may serve as a tool to identify the mechanisms underlying these associations. We examined the associations of maternal bisphenol urinary concentrations in pregnancy with neonatal metabolite profiles from cord blood.

METHODS

In a population-based prospective cohort study among 225 mother-child pairs, maternal urinary bisphenol A, S and F concentrations in first, second and third trimester were measured. LC-MS/MS was used to determine neonatal concentrations of amino acids, non-esterified fatty acids (NEFA), phospholipids (PL), and carnitines in cord blood.

RESULTS

No associations of maternal total bisphenol concentrations with neonatal metabolite profiles were present. Higher maternal average BPA concentrations were associated with higher neonatal mono-unsaturated alkyl-lysophosphatidylcholine concentrations, whereas higher maternal average BPS was associated with lower neonatal overall and saturated alkyl-lysophosphatidylcholine (p-values < 0.05).Trimester-specific analyses showed that higher maternal BPA, BPS and BPF were associated with alterations in neonatal NEFA, diacyl-phosphatidylcholines, acyl-alkyl-phosphatidylcholines, alkyl-lysophosphatidylcholine, sphingomyelines and acyl-carnitines, with the strongest effects for third trimester maternal bisphenol and neonatal diacyl-phosphatidylcholine, sphingomyeline and acyl-carnitine metabolites (p-values < 0.05). Associations were not explained by maternal socio-demographic and lifestyle characteristics or birth characteristics.

DISCUSSION

Higher maternal bisphenol A, F and S concentrations in pregnancy are associated with alterations in neonatal metabolite profile, mainly in NEFA, PL and carnitines concentrations. These findings provide novel insight into potential mechanisms underlying associations of maternal bisphenol exposure during pregnancy with adverse offspring outcomes but need to be replicated among larger, diverse populations.

Identification and Functional Characterization of Metabolites for Bone Mass in Peri- and Postmenopausal Chinese Women

CONTEXT

Although metabolic profiles appear to play an important role in menopausal bone loss, the functional mechanisms by which metabolites influence bone mineral density (BMD) during menopause are largely unknown.

OBJECTIVE

We aimed to systematically identify metabolites associated with BMD variation and their potential functional mechanisms in peri- and postmenopausal women.

DESIGN AND METHODS

We performed serum metabolomic profiling and whole-genome sequencing for 517 perimenopausal (16%) and early postmenopausal (84%) women aged 41 to 64 years in this cross-sectional study. Partial least squares regression and general linear regression analysis were applied to identify BMD-associated metabolites, and weighted gene co-expression network analysis was performed to construct co-functional metabolite modules. Furthermore, we performed Mendelian randomization analysis to identify causal relationships between BMD-associated metabolites and BMD variation. Finally, we explored the effects of a novel prominent BMD-associated metabolite on bone metabolism through both in vivo/in vitro experiments.

RESULTS

Twenty metabolites and a co-functional metabolite module (consisting of fatty acids) were significantly associated with BMD variation. We found dodecanoic acid (DA), within the identified module causally decreased total hip BMD. Subsequently, the in vivo experiments might support that dietary supplementation with DA could promote bone loss, as well as increase the osteoblast and osteoclast numbers in normal/ovariectomized mice. Dodecanoic acid treatment differentially promoted osteoblast and osteoclast differentiation, especially for osteoclast differentiation at higher concentrations in vitro (eg,10, 100 μM).

CONCLUSIONS

This study sheds light on metabolomic profiles associated with postmenopausal osteoporosis risk, highlighting the potential importance of fatty acids, as exemplified by DA, in regulating BMD.

A prospective study of maternal adiposity and glycemic traits across pregnancy and mid-childhood metabolomic profiles

BACKGROUND

Fetal exposure to maternal excess adiposity and hyperglycemia is risk factors for childhood adverse metabolic outcomes. Using data from a prospective pre-birth cohort, we aimed to further understand the prenatal determinants of fetal metabolic programming based on analyses of maternal adiposity and glycemic traits across pregnancy with childhood metabolomic profiles.

METHODS

This study included 330 mother-child pairs from the Gen3G cohort with information on maternal adiposity and glycemic markers at 5-16 (visit 1) and 24-30 (visit 2) weeks of pregnancy. At mid-childhood (4.8-7.2 years old), we collected fasting plasma and measured 1116 metabolites using an untargeted approach. We constructed networks of interconnected metabolites using a weighted-correlation network analysis algorithm. We estimated Spearman's partial correlation coefficients of maternal adiposity and glycemic traits across pregnancy with metabolite networks and individual metabolites, adjusting for maternal age, gravidity, race/ethnicity, history of smoking, and child's sex and age at blood collection for metabolite measurement.

RESULTS

We identified a network of 16 metabolites, primarily glycero-3-phosphoethanolamines (GPE) at mid-childhood that showed consistent negative correlations with maternal body mass index, waist circumference, and body-fat percentage at visits 1 and 2 (ρ_adjusted = -0.14 to -0.21) and post-challenge glucose levels at visit 2 (ρ_adjusted = -0.10 to -0.13), while positive correlations with Matsuda index (ρ_adjusted = 0.13). Within this identified network, 1-palmitoyl-2-decosahexaenoyl-GPE and 1-stearoyl-2-decosahexaenoyl-GPE appeared to be driving the associations. In addition, a network of 89 metabolites, primarily phosphatidylcholines, plasmalogens, sphingomyelins, and ceramides showed consistent negative correlations with insulin at visit 1 and post-challenge glucose at visit 2, while positive correlation with adiponectin at visit 2.

CONCLUSIONS

Prenatal exposure to maternal higher adiposity and hyperglycemic traits and lower insulin sensitivity markers were associated with a unique metabolomic pattern characterized by low serum phospho- and sphingolipids in mid-childhood.

Plasma lipidomics profile in pregnancy and gestational diabetes risk: a prospective study in a multiracial/ethnic cohort

INTRODUCTION

Disruption of lipid metabolism is implicated in gestational diabetes (GDM). However, prospective studies on lipidomics and GDM risk in race/ethnically diverse populations are sparse. Here, we aimed to (1) identify lipid networks in early pregnancy to mid-pregnancy that are associated with subsequent GDM risk and (2) examine the associations of lipid networks with glycemic biomarkers to understand the underlying mechanisms.

RESEARCH DESIGN AND METHODS

This study included 107 GDM cases confirmed using the Carpenter and Coustan criteria and 214 non-GDM matched controls from the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort, untargeted lipidomics data of 420 metabolites (328 annotated and 92 unannotated), and information on glycemic biomarkers in maternal plasma at visit 0 (10-14 weeks) and visit 1 (15-26 weeks). We constructed lipid networks using weighted correlation network analysis technique. We examined prospective associations of lipid networks and individual lipids with GDM risk using linear mixed effect models. Furthermore, we calculated Pearson's partial correlation for GDM-related lipid networks and individual lipids with plasma glucose, insulin, C-peptide and glycated hemoglobin at both study visits.

RESULTS

Lipid networks primarily characterized by elevated plasma diglycerides and short, saturated/low unsaturated triglycerides and lower plasma cholesteryl esters, sphingomyelins and phosphatidylcholines were associated with higher risk of developing GDM (false discovery rate (FDR) <0.05). Among individual lipids, 58 metabolites at visit 0 and 96 metabolites at visit 1 (40 metabolites at both time points) significantly differed between women who developed GDM and who did not (FDR <0.05). Furthermore, GDM-related lipid networks and individual lipids showed consistent correlations with maternal glycemic markers particularly in early pregnancy at visit 0.

CONCLUSIONS

Plasma lipid metabolites in early pregnancy both individually and interactively in distinct networks were associated with subsequent GDM risk in race/ethnically diverse US women. Future research is warranted to assess lipid metabolites as etiologic markers of GDM.

Developmental and Early Life Origins of Cardiometabolic Risk Factors: Novel Findings and Implications

The intent of this review is to critically consider the data that support the concept of programming and its implications. Birth weight and growth trajectories during childhood are associated with cardiometabolic disease in adult life. Both extremes, low and high birth weight coupled with postnatal growth increase the early presence of cardiometabolic risk factors and vascular imprinting, crucial elements of this framework. Data coming from epigenetics, proteomics, metabolomics, and microbiota added relevant information and contribute to better understanding of mechanisms as well as development of biomarkers helping to move forward to take actions. Research has reached a stage in which sufficiently robust data calls for new initiatives focused on early life. Prevention starting early in life is likely to have a very large impact on reducing disease incidence and its associated effects at the personal, economic, and social levels.

Integrative Analysis of Gene-Specific DNA Methylation and Untargeted Metabolomics Data from the ELEMENT Cohort

Epigenetic modifications, such as DNA methylation, influence gene expression and cardiometabolic phenotypes that are manifest in developmental periods in later life, including adolescence. Untargeted metabolomics analysis provide a comprehensive snapshot of physiological processes and metabolism and have been related to DNA methylation in adults, offering insights into the regulatory networks that influence cellular processes. We analyzed the cross-sectional correlation of blood leukocyte DNA methylation with 3758 serum metabolite features (574 of which are identifiable) in 238 children (ages 8-14 years) from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) study. Associations between these features and percent DNA methylation in adolescent blood leukocytes at LINE-1 repetitive elements and genes that regulate early life growth (IGF2, H19, HSD11B2) were assessed by mixed effects models, adjusting for sex, age, and puberty status. After false discovery rate correction (FDR q < 0.05), 76 metabolites were significantly associated with LINE-1 DNA methylation, 27 with HSD11B2, 103 with H19, and 4 with IGF2. The ten identifiable metabolites included dicarboxylic fatty acids (five associated with LINE-1 or H19 methylation at q < 0.05) and 1-octadecanoyl-rac-glycerol (q < 0.0001 for association with H19 and q = 0.04 for association with LINE-1). We then assessed the association between these ten known metabolites and adiposity 3 years later. Two metabolites, dicarboxylic fatty acid 17:3 and 5-oxo-7-octenoic acid, were inversely associated with measures of adiposity (P < .05) assessed approximately 3 years later in adolescence. In stratified analyses, sex-specific and puberty-stage specific (Tanner stage = 2 to 5 vs Tanner stage = 1) associations were observed. Most notably, hundreds of statistically significant associations were observed between H19 and LINE-1 DNA methylation and metabolites among children who had initiated puberty. Understanding relationships between subclinical molecular biomarkers (DNA methylation and metabolites) may increase our understanding of genes and biological pathways contributing to metabolic changes that underlie the development of adiposity during adolescence.

Liquid chromatography-mass spectrometry untargeted metabolomics reveals increased levels of tryptophan indole metabolites in urine of metabolic syndrome patients

Metabolic syndrome (MetS) is a multifactor condition predisposing for diabetes, cardiovascular diseases and other degenerative disorders. Although several diagnostic criteria have been established, none of them is specific and there is a call for better pathophysiological explanation of MetS and for the discovery of molecular biomarkers. Phenotype characterization at metabolome level might be useful for both purposes. To this end, our aim was to perform comparative untargeted metabolomics of urines from MetS patients and from the control group. The study participants included 52 diagnosticated and 50 healthy individuals from Leon city in central Mexico; 23 anthropometric and clinical parameters were measured and submitted to Principal Component Analysis (PCA). The obtained PCA model allowed us for selection of 11 MetS patients and 13 control subjects, correspondingly representative for each of the two groups (clearly separated in PCA). The first morning urines from these subjects were ambulatory collected and, after methanol extraction and acidification, were submitted to capillary liquid chromatography-high resolution mass spectrometry (LC-HRMS). The obtained data were analyzed on MetaboScape® platform (Bruker Daltonics). Specifically, t-test applied to LC-HRMS data revealed several ions presenting at least 3-fold higher intensities in MetS with respect to the control samples (p < 0.05). Data analysis and complementary experiments yielded the identification of the following metabolites: indole-3-acetic acid, indole-3-acetic acid-O-glucuronide, N-(indol-3-ylacetyl) glutamine, indole-3-carbaldehyde and hydroxyhexanoycarnitine. Additionally, indole-3-carboxylic acid was annotated with 2.13-fold higher abundance in MetS patients. To assess the contribution of individual metabolites in the difference between two groups of subjects, partial least square discriminant analysis was performed for LC-HRMS data and the obtained values of variable importance in projection (VIP), confirmed the association of six above mentioned compounds with MetS. Overall, this study provides direct evidence on the disturbed catabolism of tryptophan in metabolic syndrome.

Longitudinal associations of modifiable risk factors in the first 1000 days with weight status and metabolic risk in early adolescence

BACKGROUND

Many studies have identified early-life risk factors for childhood overweight/obesity (OwOb), but few have evaluated how they combine to influence later cardiometabolic health.

OBJECTIVES

We aimed to examine the association of risk factors in the first 1000 d with adiposity and cardiometabolic risk in early adolescence.

METHODS

We studied 1038 mother-child pairs in Project Viva. We chose 6 modifiable early-life risk factors previously associated with child adiposity or metabolic health in the cohort: smoking during pregnancy (yes compared with no); gestational weight gain (excessive compared with nonexcessive); sugar-sweetened beverage consumption during pregnancy (≥0.5 compared with <0.5 servings/d); breastfeeding duration (<12 compared with ≥12 mo); timing of complementary food introduction (<4 compared with ≥4 mo); and infant sleep duration (<12 compared with ≥12 h/d). We computed risk factor scores by calculating the cumulative number of risk factors for each child. In early adolescence (median: 13.1 y) we measured indicators of adiposity [BMI, fat mass index (FMI), trunk fat mass index (TFMI)]. We also calculated OwOb prevalence and metabolic syndrome (MetS) risk z score of adolescents.

RESULTS

Among 1038 adolescents, 71% had >1 early-life risk factor. In covariate-adjusted models, we observed positive monotonic increases in BMI, FMI, TFMI, and MetS z scores with increasing risk factor score. Children with 5‒6 risk factors (compared with 0-1 risk factors) had the highest risk of OwOb [risk ratio (RR): 2.53; 95% CI: 1.63, 3.91] and being in the highest MetS quartile (RR: 2.46; 95% CI: 1.43, 4.21). The predicted probability of OwOb in adolescence varied from 9.4% (favorable levels for all factors) to 63.6% (adverse levels for all factors), and for being in the highest MetS quartile from 9.6% to 56.6%.

CONCLUSIONS

Early-life risk factors in the first 1000 d cumulatively predicted higher adiposity and cardiometabolic risk in early adolescence. Intervention strategies to prevent later obesity and cardiometabolic risk may be more effective if they concurrently target multiple modifiable factors.

Precision Nutrition and Childhood Obesity: A Scoping Review

Environmental exposures such as nutrition during life stages with high developmental plasticity—in particular, the in utero period, infancy, childhood, and puberty—may have long-lasting influences on risk of chronic diseases, including obesity-related conditions that manifest as early as childhood. Yet, specific mechanisms underlying these relationships remain unclear. Here, we consider the study of ‘omics mechanisms, including nutrigenomics, epigenetics/epigenomics, and metabolomics, within a life course epidemiological framework to accomplish three objectives. First, we carried out a scoping review of population-based literature with a focus on studies that include ‘omics analyses during three sensitive periods during early life: in utero, infancy, and childhood. We elected to conduct a scoping review because the application of multi-‘omics and/or precision nutrition in childhood obesity prevention and treatment is relatively recent, and identifying knowledge gaps can expedite future research. Second, concomitant with the literature review, we discuss the relevance and plausibility of biological mechanisms that may underlie early origins of childhood obesity identified by studies to date. Finally, we identify current research limitations and future opportunities for application of multi-‘omics in precision nutrition/health practice.

Differential Effects of Post-Weaning Diet and Maternal Obesity on Mouse Liver and Brain Metabolomes

Nutritional changes during developmental windows are of particular concern in offspring metabolic disease. Questions are emerging concerning the role of maternal weight changes before conception, particularly for weight loss, in the development of diet-related disorders. Understanding the physiological pathways affected by the maternal trajectories in the offspring is therefore essential, but a broad overview is still lacking. We recently reported both metabolic and behavioral negative outcomes in offspring born to obese or weight-loss mothers and fed a control of high-fat diet, suggesting long-term modeling of metabolic pathways needing to be further characterized. Using non-targeted LC–HRMS, we investigated the impact of maternal and post-weaning metabolic status on the adult male offspring’s metabolome in three tissues involved in energy homeostasis: liver, hypothalamus and olfactory bulb. We showed that post-weaning diet interfered with the abundance of several metabolites, including 1,5-anhydroglucitol, saccharopine and β-hydroxybutyrate, differential in the three tissues. Moreover, maternal diet had a unique impact on the abundance of two metabolites in the liver. Particularly, anserine abundance, lowered by maternal obesity, was normalized by a preconceptional weight loss, whatever the post-weaning diet. This study is the first to identify a programming long-term effect of maternal preconception obesity on the offspring metabolome.

A population-based resource for intergenerational metabolomics analyses in pregnant women and their children: the Generation R Study

INTRODUCTION

Adverse exposures in early life may predispose children to cardio-metabolic disease in later life. Metabolomics may serve as a valuable tool to disentangle the metabolic adaptations and mechanisms that potentially underlie these associations.

OBJECTIVES

To describe the acquisition, processing and structure of the metabolomics data available in a population-based prospective cohort from early pregnancy onwards and to examine the relationships between metabolite profiles of pregnant women and their children at birth and in childhood.

METHODS

In a subset of 994 mothers-child pairs from a prospective population-based cohort study among pregnant women and their children from Rotterdam, the Netherlands, we used LC-MS/MS to determine concentrations of amino acids, non-esterified fatty acids, phospholipids and carnitines in blood serum collected in early pregnancy, at birth (cord blood), and at child's age 10 years.

RESULTS

Concentrations of diacyl-phosphatidylcholines, acyl-alkyl-phosphatidylcholines, alkyl-lysophosphatidylcholines and sphingomyelines were the highest in early pregnancy, concentrations of amino acids and non-esterified fatty acids were the highest at birth and concentrations of alkyl-lysophosphatidylcholines, free carnitine and acyl-carnitines were the highest at age 10 years. Correlations of individual metabolites between pregnant women and their children at birth and at the age of 10 years were low (range between r = - 0.10 and r = 0.35).

CONCLUSION

Our results suggest that unique metabolic profiles are present among pregnant women, newborns and school aged children, with limited intergenerational correlations between metabolite profiles. These data will form a valuable resource to address the early metabolic origins of cardio-metabolic disease.

Prepregnant Obesity of Mothers in a Multiethnic Cohort Is Associated with Cord Blood Metabolomic Changes in Offspring

Maternal obesity has become a growing global health concern that may predispose the offspring to medical conditions later in life. However, the metabolic link between maternal prepregnant obesity and healthy offspring has not yet been fully elucidated. In this study, we conducted a case-control study using a coupled untargeted and targeted metabolomic approach from the newborn cord blood metabolomes associated with a matched maternal prepregnant obesity cohort of 28 cases and 29 controls. The subjects were recruited from multiethnic populations in Hawaii, including rarely reported Native Hawaiian and other Pacific Islanders (NHPI). We found that maternal obesity was the most important factor contributing to differences in cord blood metabolomics. Using an elastic net regularization-based logistic regression model, we identified 29 metabolites as potential early-life biomarkers manifesting intrauterine effect of maternal obesity, with accuracy as high as 0.947 after adjusting for clinical confounding (maternal and paternal age, ethnicity, parity, and gravidity). We validated the model results in a subsequent set of samples (N = 30) with an accuracy of 0.822. Among the metabolites, six metabolites (galactonic acid, butenylcarnitine, 2-hydroxy-3-methylbutyric acid, phosphatidylcholine diacyl C40:3, 1,5-anhydrosorbitol, and phosphatidylcholine acyl-alkyl 40:3) were individually and significantly different between the maternal obese and normal-weight groups. Interestingly, hydroxy-3-methylbutyric acid showed significantly higher levels in cord blood from the NHPI group compared to that from Asian and Caucasian groups. In summary, significant associations were observed between maternal prepregnant obesity and offspring metabolomic alternation at birth, revealing the intergenerational impact of maternal obesity.

A prospective study of associations between in utero exposure to gestational diabetes mellitus and metabolomic profiles during late childhood and adolescence

AIMS/HYPOTHESIS

This study aimed to: (1) identify metabolite patterns during late childhood that differ with respect to exposure to maternal gestational diabetes mellitus (GDM); (2) examine the persistence of GDM/metabolite associations 5 years later, during adolescence; and (3) investigate the associations of metabolite patterns with adiposity and metabolic biomarkers from childhood through adolescence.

METHODS

This study included 592 mother-child pairs with information on GDM exposure (n = 92 exposed), untargeted metabolomics data at age 6-14 years (T1) and at 12-19 years (T2), and information on adiposity and metabolic risk biomarkers at T1 and T2. We first consolidated 767 metabolites at T1 into factors (metabolite patterns) via principal component analysis (PCA) and used multivariable regression to identify factors that differed by GDM exposure, at α = 0.05. We then examined associations of GDM with individual metabolites within factors of interest at T1 and T2, and investigated associations of GDM-related factors at T1 with adiposity and metabolic risk throughout T1 and T2 using mixed-effects linear regression models.

RESULTS

Of the six factors retained from PCA, GDM exposure was associated with greater odds of being in quartile (Q)4 (vs Q1-3) of 'Factor 4' at T1 after accounting for age, sex, race/ethnicity, maternal smoking habits during pregnancy, Tanner stage, physical activity and total energy intake, at α = 0.05 (OR 1.78 [95% CI 1.04, 3.04]; p = 0.04). This metabolite pattern comprised phosphatidylcholines, diacylglycerols and phosphatidylethanolamines. GDM was consistently associated with elevations in a subset of individual compounds within this pattern at T1 and T2. While this metabolite pattern was not related to the health outcomes in boys, it corresponded with greater adiposity and a worse metabolic profile among girls throughout the follow-up period. Each 1-unit increment in Factor 4 corresponded with 0.17 (0.08, 0.25) units higher BMI z score, 8.83 (5.07, 12.59) pmol/l higher fasting insulin, 0.28 (0.13, 0.43) units higher HOMA-IR, and 4.73 (2.15, 7.31) nmol/l higher leptin.

CONCLUSIONS/INTERPRETATION

Exposure to maternal GDM was nominally associated with a metabolite pattern characterised by elevated serum phospholipids in late childhood and adolescence at α = 0.05. This metabolite pattern was associated with greater adiposity and metabolic risk among female offspring throughout the late childhood-to-adolescence transition. Future studies are warranted to confirm our findings.

Metabolomics Analytics Workflow for Epidemiological Research: Perspectives from the Consortium of Metabolomics Studies (COMETS)

The application of metabolomics technology to epidemiological studies is emerging as a new approach to elucidate disease etiology and for biomarker discovery. However, analysis of metabolomics data is complex and there is an urgent need for the standardization of analysis workflow and reporting of study findings. To inform the development of such guidelines, we conducted a survey of 47 cohort representatives from the Consortium of Metabolomics Studies (COMETS) to gain insights into the current strategies and procedures used for analyzing metabolomics data in epidemiological studies worldwide. The results indicated a variety of applied analytical strategies, from biospecimen and data pre-processing and quality control to statistical analysis and reporting of study findings. These strategies included methods commonly used within the metabolomics community and applied in epidemiological research, as well as novel approaches to pre-processing pipelines and data analysis. To help with these discrepancies, we propose use of open-source initiatives such as the online web-based tool COMETS Analytics, which includes helpful tools to guide analytical workflow and the standardized reporting of findings from metabolomics analyses within epidemiological studies. Ultimately, this will improve the quality of statistical analyses, research findings, and study reproducibility.

Are we close to defining a metabolomic signature of human obesity? A systematic review of metabolomics studies

INTRODUCTION

Obesity is a disorder characterized by a disproportionate increase in body weight in relation to height, mainly due to the accumulation of fat, and is considered a pandemic of the present century by many international health institutions. It is associated with several non-communicable chronic diseases, namely, metabolic syndrome, type 2 diabetes mellitus (T2DM), cardiovascular diseases (CVD), and cancer. Metabolomics is a useful tool to evaluate changes in metabolites due to being overweight and obesity at the body fluid and cellular levels and to ascertain metabolic changes in metabolically unhealthy overweight and obese individuals (MUHO) compared to metabolically healthy individuals (MHO).

OBJECTIVES

We aimed to conduct a systematic review (SR) of human studies focused on identifying metabolomic signatures in obese individuals and obesity-related metabolic alterations, such as inflammation or oxidative stress.

METHODS

We reviewed the literature to identify studies investigating the metabolomics profile of human obesity and that were published up to May 7th, 2019 in SCOPUS and PubMed through an SR. The quality of reporting was evaluated using an adapted of QUADOMICS.

RESULTS

Thirty-three articles were included and classified according to four types of approaches. (i) studying the metabolic signature of obesity, (ii) studying the differential responses of obese and non-obese subjects to dietary challenges (iii) studies that used metabolomics to predict weight loss and aimed to assess the effects of weight loss interventions on the metabolomics profiles of overweight or obese human subjects (iv) articles that studied the effects of specific dietary patterns or dietary compounds on obesity-related metabolic alterations in humans.

CONCLUSION

The present SR provides state-of-the-art information about the use of metabolomics as an approach to understanding the dynamics of metabolic processes involved in human obesity and emphasizes metabolic signatures related to obesity phenotypes.

An individual participant data meta-analysis on metabolomics profiles for obesity and insulin resistance in European children

Childhood obesity prevalence is rising in countries worldwide. A variety of etiologic factors contribute to childhood obesity but little is known about underlying biochemical mechanisms. We performed an individual participant meta-analysis including 1,020 pre-pubertal children from three European studies and investigated the associations of 285 metabolites measured by LC/MS-MS with BMI z-score, height, weight, HOMA, and lipoprotein concentrations. Seventeen metabolites were significantly associated with BMI z-score. Sphingomyelin (SM) 32:2 showed the strongest association with BMI z-score (P = 4.68 × 10⁻²³) and was also closely related to weight, and less strongly to height and LDL, but not to HOMA. Mass spectrometric analyses identified SM 32:2 as myristic acid containing SM d18:2/14:0. Thirty-five metabolites were significantly associated to HOMA index. Alanine showed the strongest positive association with HOMA (P = 9.77 × 10⁻¹⁶), while acylcarnitines and non-esterified fatty acids were negatively associated with HOMA. SM d18:2/14:0 is a powerful marker for molecular changes in childhood obesity. Tracing back the origin of SM 32:2 to dietary source in combination with genetic predisposition will path the way for early intervention programs. Metabolic profiling might facilitate risk prediction and personalized interventions in overweight children.

Metabolomic profiles and development of metabolic risk during the pubertal transition: a prospective study in the ELEMENT Project

OBJECTIVES

(1) Examine associations of a branched-chain amino acid (BCAA) metabolite pattern with metabolic risk across adolescence; (2) use Least Absolute Shrinkage and Selection Operator (LASSO) to identify novel metabolites of metabolic risk.

METHODS

We used linear regression to examine associations of a BCAA score with change (∆) in metabolic biomarkers over 5-year follow-up in 179 adolescents 8-14 years at baseline. Next, we applied LASSO, a regularized regression technique well suited for reduction of high-dimensional data, to identify metabolite predictors of ∆biomarkers.

RESULTS

In boys, the BCAA score corresponded with decreasing C-peptide, C-peptide-based insulin resistance (CP-IR), total cholesterol (TC), and low-density-lipoprotein cholesterol (LDL). In pubertal girls, the BCAA pattern corresponded with increasing C-peptide and leptin. LASSO identified asparagine as a predictor of decreasing C-peptide (β = -0.33) and CP-IR (β = -0.012), and acetyl-carnitine (β = 2.098), 4-hydroxyproline (β = -0.050), ornithine (β = -0.353), and α-aminoisobutyric acid (β = -0.793) as determinants of TC in boys. In girls, histidine was a negative determinant of TC (β = -0.033).

CONCLUSIONS

The BCAA pattern was associated with ∆glycemia and ∆lipids in a sex-specific manner. LASSO identified asparagine, which influences growth hormone secretion, as a determinant of decreasing C-peptide and CP-IR in boys, and metabolites on lipid metabolism pathways as determinants of decreasing cholesterol in both sexes.

Instability of personal human metabotype is linked to all-cause mortality

Disruption of metabolic homeostasis is an important factor in many diseases. Various metabolites have been linked to higher risk of morbidity and all-cause mortality using metabolomics in large population-based cohorts. In these studies, baseline metabolite levels were compared across subjects to identify associations with health outcomes, implying the existence of 'healthy' concentration ranges that are equally applicable to all individuals. Here, we focused on intra-individual changes in metabolite levels over time and their link to mortality, potentially allowing more personalized risk assessment. We analysed targeted metabolomics data for 134 blood metabolites from 1409 participants in the population-based CARLA cohort at baseline and after four years. Metabotypes of the majority of participants (59%) were extremely stable over time indicated by high correlation between the subjects' metabolite profiles at the two time points. Metabotype instability and, in particular, decrease of valine were associated with higher risk of all-cause mortality in 7.9 years of follow-up (hazard ratio (HR) = 1.5(95%CI = 1.0-2.3) and 0.2(95%CI = 0.1-0.3)) after multifactorial adjustment. Excluding deaths that occurred in the first year after metabolite profiling showed similar results (HR = 1.8(95%CI = 1.1-2.8)). Lower metabotype stability was also associated with incident cardiovascular disease (OR = 1.2(95%CI = 1.0-1.3)). Therefore, changes in the personal metabotype might be a valuable indicator of pre-clinical disease.

Maternal Metabolomic Profile and Fetal Programming of Offspring Adiposity: Identification of Potentially Protective Lipid Metabolites

SCOPE

The fetal programming paradigm posits that the origins of obesity can be traced, in part, to the intrauterine period of life. However, the mechanisms underlying fetal programming are not well understood, and few studies have measured offspring adiposity in the neonatal period. The aim of this study is to identify maternal metabolites, and their determinants, that are associated with neonatal adiposity.

METHODS AND RESULTS

A targeted metabolomics approach is applied to analyze plasma samples collected across gestation from a well-characterized cohort of 253 pregnant women participating in a prospective study at the University of California, Irvine. Whole-body dual X-ray absorptiometry (DXA) imaging of body composition is obtained in N = 121 newborns. Statistical models are adjusted for potential confounders and multiple testing. The authors identify six alkyl-linked phosphatidylcholines (PCae), containing fatty acid 20:4, that are significantly and negatively associated with neonatal body fat percentage. Factors indicating higher socioeconomic status, non-Hispanic ethnicity, and higher nonesterified fatty acid percentages are positively associated with these PCae.

CONCLUSIONS

The polyunsaturated fatty acid 20:4 contained in PCae may exert a beneficial effect with respect to future propensity for obesity development. Prepregnancy and early pregnancy factors are determinants of these PCae, highlighting the importance of addressing preconceptional conditions for fetal programming of newborn adiposity.

Metabolic phenotyping of malnutrition during the first 1000 days of life

Nutritional restrictions during the first 1000 days of life can impair or delay the physical and cognitive development of the individual and have long-term consequences for their health. Metabolic phenotyping (metabolomics/metabonomics) simultaneously measures a diverse range of low molecular weight metabolites in a sample providing a comprehensive assessment of the individual's biochemical status. There are a growing number of studies applying such approaches to characterize the metabolic derangements induced by various forms of early-life malnutrition. This includes acute and chronic undernutrition and specific micronutrient deficiencies. Collectively, these studies highlight the diverse and dynamic metabolic disruptions resulting from various forms of nutritional deficiencies. Perturbations were observed in many pathways including those involved in energy, amino acid, and bile acid metabolism, the metabolic interactions between the gut microbiota and the host, and changes in metabolites associated with gut health. The information gleaned from such studies provides novel insights into the mechanisms linking malnutrition with developmental impairments and assists in the elucidation of candidate biomarkers to identify individuals at risk of developmental shortfalls. As the metabolic profile represents a snapshot of the biochemical status of an individual at a given time, there is great potential to use this information to tailor interventional strategies specifically to the metabolic needs of the individual.

Greater Neonatal Fat-Free Mass and Similar Fat Mass Following a Randomized Trial to Control Excess Gestational Weight Gain

OBJECTIVE

The objective of this study was to determine the effectiveness of controlling maternal gestational weight gain (GWG) in the second and third trimesters on neonate body composition.

METHODS

Two hundred ten healthy women with overweight (25 > BMI < 30) or obesity (BMI ≥ 30) were randomly assigned to a lifestyle intervention (LI) program focused on controlling GWG through nutrition and activity behaviors or to usual obstetrical care (UC). Infant fat and fat-free mass (FFM) at birth were measured by using air displacement plethysmography (PEA POD) and by using quantitative magnetic resonance (QMR).

RESULTS

At baseline, there were no between-group differences in maternal characteristics (mean [SD]): age: 33.8 (4.3) years, weight: 81.9 (13.7) kg, BMI: 30.4 (4.5), and gestational age at randomization: 14.9 (0.8) weeks. GWG was less in the LI group by 1.79 kg (P = 0.003) or 0.0501 kg/wk (P = 0.002). Compared with UC infants, LI infants had greater weight (131 ± 59 g P = 0.03), FFM (98 ± 45 g; P = 0.03) measured by PEA POD, and lean mass (105 ± 38 g; P = 0.006) measured by QMR. Fat mass and percent fat were not significantly different.

CONCLUSIONS

Intervening in women with overweight and obesity through behaviors promoting healthy diet and physical activity to control GWG resulted in neonates with similar fat and greater FFM.

Cord Metabolic Profiles in Obese Pregnant Women: Insights Into Offspring Growth and Body Composition

Context

Offspring exposed in utero to maternal obesity have an increased risk of later obesity; however, the underlying mechanisms remain unknown.

Objective

To assess the effect of an antenatal lifestyle intervention in obese women on the offspring's cord blood metabolic profile and to examine associations of the cord blood metabolic profile with maternal clinical characteristics and offspring anthropometry at birth and age 6 months.

Design

Randomized controlled trial and cohort study.

Setting

The UK Pregnancies Better Eating and Activity Trial.

Participants

Three hundred forty-four mother-offspring pairs.

Intervention

Antenatal behavioral lifestyle (diet and physical activity) intervention.

Main Outcome Measures

Targeted cord blood metabolic profile, including candidate hormone and metabolomic analyses.

Results

The lifestyle intervention was not associated with change in the cord blood metabolic profile. Higher maternal glycemia, specifically fasting glucose at 28 weeks gestation, had a linear association with higher cord blood concentrations of lysophosphatidylcholines (LPCs) 16.1 (β = 0.65; 95% confidence interval: 0.03 to 0.10) and 18.1 (0.52; 0.02 to 0.80), independent of the lifestyle intervention. A principal component of cord blood phosphatidylcholines and LPCs was associated with infant z scores of birth weight (0.04; 0.02 to 0.07) and weight at age 6 months (0.05; 0.00 to 0.10). Cord blood insulin growth factor (IGF)-1 and adiponectin concentrations were positively associated with infant weight z score at birth and at 6 months.

Conclusions

Concentrations of LPCs and IGF-1 in cord blood are related to infant weight. These findings support the hypothesis that susceptibility to childhood obesity may be programmed in utero, but further investigation is required to establish whether these associations are causally related.

Assessing the consequences of gestational diabetes mellitus on offspring's cardiovascular health: MySweetHeart Cohort study protocol, Switzerland

INTRODUCTION

Gestational diabetes mellitus (GDM) is a state of glucose intolerance with onset during pregnancy. GDM carries prenatal and perinatal risks as well as long-term risks for the mother and her child. GDM may be involved in the foetal programming of long-term cardiovascular health. However, evidence is sparse and the effect of GDM on cardiovascular health is unknown. To address these issues, we will conduct MySweetHeart Cohort study. The objectives are to assess the effect of GDM on offspring's cardiovascular health early in life by using surrogate markers of cardiovascular disease and atherosclerosis.

METHODS AND ANALYSIS

This is a cohort study of 100 offspring of women with GDM and 100 offspring of women without GDM. At inclusion, a baseline assessment of the mothers will be conducted through means of self-report questionnaires, a researcher-administrated interview, blood pressure and anthropometric measurements, and a maternal blood sampling. Between the 30th and 34th weeks of gestation, a foetal echography will be performed to assess the foetal cardiac structure and function, the fetomaternal circulation and the hepatic volume. At birth, maternal and neonatal characteristics will be assessed. An echocardiography will be performed to assess cardiac structure and function 2-7 days after birth; carotid intima-media thickness will be also measured to assess vascular structure. MySweetHeart Cohort is linked to MySweetHeart Trial (clinicaltrials.gov/ct2/show/NCT02890693), a randomised controlled trial assessing the effect of a multidimensional interdisciplinary lifestyle and psychosocial intervention to improve the cardiometabolic and mental health of women with GDM and their offspring. A long-term follow-up of children is planned.

ETHICS AND DISSEMINATION

Ethical approval has been obtained through the state Human Research Ethics Committee of the Canton de Vaud (study number 2016-00745). We aim to disseminate the findings through regional, national and international conferences and through peer-reviewed journals.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov (clinicaltrials.gov/ct2/show/NCT02872974).

Impairment of microvascular angiogenesis is associated with delay in prostatic development in rat offspring of maternal protein malnutrition

Experimental data demonstrated the negative impact of maternal protein malnutrition (MPM) on rat prostate development, but the mechanism behind the impairment of prostate growth has not been well understood. Male Sprague Dawley rats, borned to dams fed a normal protein diet (CTR group, 17% protein diet), were compared with those borned from dams fed a low protein diet (6% protein diet) during gestation (GLP group) or gestation and lactation (GLLP). The ventral prostate lobes (VP) were removed at post-natal day (PND) 10 and 21, and analyzed via different methods. The main findings were low birth weight, a reduction in ano-genital distance (AGD, a testosterone-dependent parameter), and an impairment of prostate development. A delay in prostate morphogenesis was associated with a reduced testosterone levels and angiogenic process through downregulation of aquaporin-1 (AQP-1), insulin/IGF-1 axis and VEGF signaling pathway. Depletion of the microvascular network, which occurs in parallel to the impairment of proliferation and differentiation of the epithelial cells, affects the bidirectional flux between blood vessels impacting prostatic development. In conclusion, our data support the hypothesis that a reduction in microvascular angiogenesis, especially in the subepithelial compartment, is associated to the impairment of prostate morphogenesis in the offspring of MPM dams.

Investigating the early metabolic fingerprint of celiac disease - a prospective approach

OBJECTIVES AND STUDY

In the development of Celiac Disease (CD) both genetic and environmental factors play a crucial role. The Human Leukocyte Antigen (HLA)-DQ2 and HLA-DQ8 loci are strongly related to the disease and are necessary but not sufficient for the development of CD. Therefore, increasing interest lies in examining the mechanisms of CD onset from the early beginning. Differences in serum and urine metabolic profiles between healthy individuals and CD patients have been reported previously. We aimed to investigate if the metabolic pathways were already altered in young, 4 month old infants, preceding the CD diagnosis.

METHODS

Serum samples were available for 230 four month old infants of the PreventCD project, a multicenter, randomized, double-blind, dietary intervention study. All children were positive for HLA-DQ2 and/or HLA-DQ8 and had at least one first-degree relative diagnosed with CD. Amino acids were quantified after derivatization with liquid chromatography - tandem mass spectrometry (MS/MS) and polar lipid concentrations (acylcarnitines, lysophosphatidylcholines, phosphatidylcholines, and sphingomyelins) were determined with direct infusion MS/MS. We investigated the association of the metabolic profile with (1) the development of CD up to the age of 8 years (yes/no), (2) with HLA-risk groups, (3) with the age at CD diagnosis, using linear mixed models and cox proportional hazards models. Gender, intervention group, and age at blood withdrawal were included as potential confounder.

RESULTS

By the end of 2014, thirty-three out of the 230 children (14%) were diagnosed with CD according to the ESPGHAN criteria. Median age at diagnosis was 3.4 years (IQR, 2.4-5.2). Testing each metabolite for a difference in the mean between healthy and CD children, we (1) could not identify a discriminant analyte or a pattern pointing towards an altered metabolism (Bonferroni corrected P > 0.05 for all). Metabolite concentrations (2) did not differ across the HLA-risk groups. When investigating the age at diagnosis using (3) survival models, we found no evidence for an association between the metabolic profile and the risk of a later CD diagnosis.

CONCLUSION

The metabolic profile at 4 months of age was not predictive for the development of CD up to the age of 8 years. Our results suggest that metabolic pathways reflected in serum are affected only later in life and that the HLA-genotype does not influence the serum metabolic profile in young infants before introduction of solid food.

Developmental cigarette smoke exposure II: Hepatic proteome profiles in 6 month old adult offspring

Utilizing a mouse model of 'active' developmental cigarette smoke exposure (CSE) [gestational day (GD) 1 through postnatal day (PD) 21] characterized by offspring low birth weight, the impact of developmental CSE on liver proteome profiles of adult offspring at 6 months of age was determined. Liver tissue was collected from Sham- and CSE-offspring for 2D-SDS-PAGE based proteome analysis with Partial Least Squares-Discriminant Analysis (PLS-DA). A similar study conducted at the cessation of exposure to cigarette smoke documented decreased gluconeogenesis coupled to oxidative stress in weanling offspring. In the current study, exposure throughout development to cigarette smoke resulted in impaired hepatic carbohydrate metabolism, decreased serum glucose levels, and increased gluconeogenic regulatory enzyme abundances during the fed-state coupled to decreased expression of SIRT1 as well as increased PEPCK and PGC1α expression. Together these findings indicate inappropriately timed gluconeogenesis that may reflect impaired insulin signaling in mature offspring exposed to 'active' developmental CSE.