Maternal Diet and the Serum Metabolome in Pregnancy: Robust Dietary Biomarkers Generalizable to a Multiethnic Birth Cohort

Calibration of citrus intake assessed by food frequency questionnaires using urinary proline betaine in an observational study setting

BACKGROUND

Whether observational study can be employed to establish calibration equations for self-reported dietary intake using food biomarkers is unknown.

OBJECTIVES

This study aims to demonstrate the feasibility of obtaining calibration equations based on food biomarkers and 7-d diet records (7DDRs) to correct measurement errors of food frequency questionnaires (FFQs) in an observational study setting.

METHODS

The study population consisted of 669 males and 749 females from the Women's and Men's Lifestyle Validation Studies. In the training set, the biomarker-predicted intake derived by regressing 7DDR-assessed intake on urinary proline betaine concentration was regressed on the FFQ-assessed intake to obtain the calibration equations. The regression coefficients were applied to the test set to calculate the calibrated FFQ intake. We examined total citrus as well as individual citrus fruits/beverages.

RESULTS

Urinary proline betaine was moderately correlated with orange juice intake (Pearson correlation [r] = 0.53 for 7DDR and 0.48 for FFQ) but only weakly correlated with intakes of orange (r = 0.12 for 7DDR and 0.15 for FFQ) and grapefruit (r = 0.14 for 7DDR and 0.09 for FFQ). The FFQ-assessed citrus intake was systematically higher than the 7DDR-assessed intake, and after calibrations, the mean calibrated FFQ measurements were almost identical to 7DDR assessments. In the test set, the mean intake levels from 7DDRs, FFQs, and calibrated FFQs were 62.5, 75.3, and 63.2 g/d for total citrus; 41.6, 42.5, and 41.9 g/d for orange juice; 11.8, 24.3, and 12.3 g/d for oranges; and 8.3, 9.3, and 8.6 g/d for grapefruit, respectively. We observed larger differences between calibrated FFQ and 7DDR assessments at the extreme ends of intake, although, on average, good agreements were observed for all citrus except grapefruit.

CONCLUSIONS

Our 2-step calibration approach has the potential to be adapted to correct systematic measurement error for other foods/nutrients with established food biomarkers in a cost effective way.

The association of red and processed meat with gestational diabetes mellitus: Results from 2 Canadian birth cohort studies

OBJECTIVE

Red and processed meat is considered risk factors of gestational diabetes mellitus (GDM), but the evidence is inconclusive. We aimed to examine the association between red and processed meat intake and odds of GDM among South Asian and White European women living in Canada.

METHODS

This is a cross-sectional analysis of pregnant women from two birth cohorts: SouTh Asian biRth cohorT (START; n = 976) and Family Atherosclerosis Monitoring In earLY life (FAMILY; n = 581). Dietary intake was assessed using a validated 169-item semi-quantitative food-frequency questionnaire (FFQ). Multivariate logistic regression models were used to examine the associations between gestational diabetes and: 1) total red and processed meat; 2) unprocessed red meat; 3) processed meat and GDM after adjustment for potential confounders.

RESULTS

There were 241 GDM cases in START and 91 in FAMILY. The median total red and processed meat intake were 1.5 g/d (START) and 52.8 g/d (FAMILY). In START, the multivariable-adjusted odds ratio (OR) showed neither lower nor higher intakes of unprocessed red meat (p-trend = 0.68), processed meat (p-trend = 0.90), or total red and processed meat (p-trend = 0.44), were associated with increased odds of GDM, when compared with medium intake. Similar results were observed in FAMILY except for processed meat intake [OR = 0.94 (95% CI 0.47-1.91), for medium versus low and OR = 1.51 (95% CI 0.77-2.29) for medium versus high; p-trend = 0.18] after adjusting for additional dietary factors such as the diet quality score, total fiber, saturated fat and glycemic load.

CONCLUSION

Medium compared with low or high red and processed meat intake is not associated with GDM in White Europeans and South Asians living in Canada.

Understanding the impact of maternal and infant nutrition on infant/child health: multiethnic considerations, knowledge translation, and future directions for equitable health research

A mother's intrauterine environment influences her health and that of her offspring, at birth and in the future. Herein, we present an overview of our Canadian Institutes of Health Research (CIHR)-funded grant "Understanding the impact of maternal and infant nutrition on infant/child health"-set within The NutriGen Birth Cohort Alliance. NutriGen is a consortium of four Canadian prospective birth cohorts representing >5000 mother-child pairs of diverse ethnic groups including South Asians, White Europeans, and Indigenous peoples. We summarize our objectives and main findings on outcomes of maternal diet, gestational diabetes, birth weight, cardiometabolic health, the microbiome, and epigenetic modifications. We append this work with 10 key messages when conducting multiethnic research and review our knowledge translation products. We describe the clinical impact of our research on maternal and child health and conclude with future directions on biomarker discovery, expansion to other ethnic groups, and interventions for high-risk populations.

Biomarker Candidates of Habitual Food Intake in a Swedish Cohort of Pregnant and Lactating Women and Their Infants

Circulating food metabolites could improve dietary assessments by complementing traditional methods. Here, biomarker candidates of food intake were identified in plasma samples from pregnancy (gestational week 29, N = 579), delivery (mothers, N = 532; infants, N = 348), and four months postpartum (mothers, N = 477; breastfed infants, N = 193) and associated to food intake assessed with semi-quantitative food frequency questionnaires. Families from the Swedish birth cohort Nutritional impact on Immunological maturation during Childhood in relation to the Environment (NICE) were included. Samples were analyzed using untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. Both exposure and outcome were standardized, and relationships were investigated using a linear regression analysis. The intake of fruits and berries and fruit juice were both positively related to proline betaine levels during pregnancy (fruits and berries, β = 0.23, FDR < 0.001; fruit juice, β = 0.27, FDR < 0.001), at delivery (fruit juice, infants: β = 0.19, FDR = 0.028), and postpartum (fruits and berries, mothers: β = 0.27, FDR < 0.001, infants: β = 0.29, FDR < 0.001; fruit juice, mothers: β = 0.37, FDR < 0.001). Lutein levels were positively related to vegetable intake during pregnancy (β = 0.23, FDR < 0.001) and delivery (mothers: β = 0.24, FDR < 0.001; newborns: β = 0.18, FDR = 0.014) and CMPF with fatty fish intake postpartum (mothers: β = 0.20, FDR < 0.001). No clear relationships were observed with the expected food sources of the remaining metabolites (acetylcarnitine, choline, indole-3-lactic acid, pipecolic acid). Our study suggests that plasma lutein could be useful as a more general food group intake biomarker for vegetables and fruits during pregnancy and delivery. Also, our results suggest the application of proline betaine as an intake biomarker of citrus fruit during gestation and lactation.

Serum Metabolomic Markers of Protein-Rich Foods and Incident CKD: Results From the Atherosclerosis Risk in Communities Study

Rationale & Objective

While urine excretion of nitrogen estimates the total protein intake, biomarkers of specific dietary protein sources have been sparsely studied. Using untargeted metabolomics, this study aimed to identify serum metabolomic markers of 6 protein-rich foods and to examine whether dietary protein-related metabolites are associated with incident chronic kidney disease (CKD).

Study Design

Prospective cohort study.

Setting & Participants

A total of 3,726 participants from the Atherosclerosis Risk in Communities study without CKD at baseline.

Exposures

Dietary intake of 6 protein-rich foods (fish, nuts, legumes, red and processed meat, eggs, and poultry), serum metabolites.

Outcomes

Incident CKD (estimated glomerular filtration rate < 60 mL/min/1.73 m2 with ≥25% estimated glomerular filtration rate decline relative to visit 1, hospitalization or death related to CKD, or end-stage kidney disease).

Analytical Approach

Multivariable linear regression models estimated cross-sectional associations between protein-rich foods and serum metabolites. C statistics assessed the ability of the metabolites to improve the discrimination of highest versus lower 3 quartiles of intake of protein-rich foods beyond covariates (demographics, clinical factors, health behaviors, and the intake of nonprotein food groups). Cox regression models identified prospective associations between protein-related metabolites and incident CKD.

Results

Thirty significant associations were identified between protein-rich foods and serum metabolites (fish, n = 8; nuts, n = 5; legumes, n = 0; red and processed meat, n = 5; eggs, n = 3; and poultry, n = 9). Metabolites collectively and significantly improved the discrimination of high intake of protein-rich foods compared with covariates alone (difference in C statistics = 0.033, 0.051, 0.003, 0.024, and 0.025 for fish, nuts, red and processed meat, eggs, and poultry-related metabolites, respectively; P < 1.00 × 10-16 for all). Dietary intake of fish was positively associated with 1-docosahexaenoylglycerophosphocholine (22:6n3), which was inversely associated with incident CKD (HR, 0.82; 95% CI, 0.75-0.89; P = 7.81 × 10-6).

Limitations

Residual confounding and sample-storage duration.

Conclusions

We identified candidate biomarkers of fish, nuts, red and processed meat, eggs, and poultry. A fish-related metabolite, 1-docosahexaenoylglycerophosphocholine (22:6n3), was associated with a lower risk of CKD.

Plasma Metabolomics of Dietary Intake of Protein-Rich Foods and Kidney Disease Progression in Children

OBJECTIVE

Evidence regarding the efficacy of a low-protein diet for patients with CKD is inconsistent and recommending a low-protein diet for pediatric patients is controversial. There is also a lack of objective biomarkers of dietary intake. The purpose of this study was to identify plasma metabolites associated with dietary intake of protein and to assess whether protein-related metabolites are associated with CKD progression.

METHODS

Nontargeted metabolomics was conducted in plasma samples from 484 Chronic Kidney Disease in Children (CKiD) participants. Multivariable linear regression estimated the cross-sectional association between 949 known, nondrug metabolites and dietary intake of total protein, animal protein, plant protein, chicken, dairy, nuts and beans, red and processed meat, fish, and eggs, adjusting for demographic, clinical, and dietary covariates. Cox proportional hazards models assessed the prospective association between protein-related metabolites and CKD progression defined as the initiation of kidney replacement therapy or 50% eGFR reduction, adjusting for demographic and clinical covariates.

RESULTS

One hundred and twenty-seven (26%) children experienced CKD progression during 5 years of follow-up. Sixty metabolites were significantly associated with dietary protein intake. Among the 60 metabolites, 10 metabolites were significantly associated with CKD progression (animal protein: n = 1, dairy: n = 7, red and processed meat: n = 2, nuts and beans: n = 1), including one amino acid, one cofactor and vitamin, 4 lipids, 2 nucleotides, one peptide, and one xenobiotic. 1-(1-enyl-palmitoyl)-2-oleoyl-glycerophosphoethanolamine (GPE, P-16:0/18:1) was positively associated with dietary intake of red and processed meat, and a doubling of its abundance was associated with 88% higher risk of CKD progression. 3-ureidopropionate was inversely associated with dietary intake of red and processed meat, and a doubling of its abundance was associated with 48% lower risk of CKD progression.

CONCLUSIONS

Untargeted plasma metabolomic profiling revealed metabolites associated with dietary intake of protein and CKD progression in a pediatric population.

Plasma metabolomics profiles in Black and White participants of the Adventist Health Study-2 cohort

BACKGROUND

Black Americans suffer disparities in risk for cardiometabolic and other chronic diseases. Findings from the Adventist Health Study-2 (AHS-2) cohort have shown associations of plant-based dietary patterns and healthy lifestyle factors with prevention of such diseases. Hence, it is likely that racial differences in metabolic profiles correlating with disparities in chronic diseases are explained largely by diet and lifestyle, besides social determinants of health.

METHODS

Untargeted plasma metabolomics screening was performed on plasma samples from 350 participants of the AHS-2, including 171 Black and 179 White participants, using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and a global platform of 892 metabolites. Differences in metabolites or biochemical subclasses by race were analyzed using linear regression, considering various models adjusted for known confounders, dietary and/or other lifestyle behaviors, social vulnerability, and psychosocial stress. The Storey permutation approach was used to adjust for false discovery at FDR < 0.05.

RESULTS

Linear regression revealed differential abundance of over 40% of individual metabolites or biochemical subclasses when comparing Black with White participants after adjustment for false discovery (FDR < 0.05), with the vast majority showing lower abundance in Blacks. Associations were not appreciably altered with adjustment for dietary patterns and socioeconomic or psychosocial stress. Metabolite subclasses showing consistently lower abundance in Black participants included various lipids, such as lysophospholipids, phosphatidylethanolamines, monoacylglycerols, diacylglycerols, and long-chain monounsaturated fatty acids, among other subclasses or lipid categories. Among all biochemical subclasses, creatine metabolism exclusively showed higher abundance in Black participants, although among metabolites within this subclass, only creatine showed differential abundance after adjustment for glomerular filtration rate. Notable metabolites in higher abundance in Black participants included methyl and propyl paraben sulfates, piperine metabolites, and a considerable proportion of acetylated amino acids, including many previously found associated with glomerular filtration rate.

CONCLUSIONS

Differences in metabolic profiles were evident when comparing Black and White participants of the AHS-2 cohort. These differences are likely attributed in part to dietary behaviors not adequately explained by dietary pattern covariates, besides other environmental or genetic factors. Alterations in these metabolites and associated subclasses may have implications for the prevention of chronic diseases in Black Americans.

An epidemiological introduction to human metabolomic investigations

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Maternal Dietary Protein Patterns and Neonatal Anthropometrics: A Prospective Study with Insights from NMR Metabolomics in Amniotic Fluid

This study aimed to characterize dietary protein patterns (DPPs) in a sample pool of 298 well-nourished pregnant women and explore potential associations between DPPs and neonatal anthropometrics. Maternal dietary data were collected using a validated food frequency questionnaire. Neonatal anthropometrics were abstracted from health booklets. A hierarchical cluster analysis identified three DPPs: "Dairy-focused", "Med-fusion", and "Traditional-inspired". The "Dairy-focused" DPP exhibited the highest protein intake (p < 0.001), predominantly animal protein (p < 0.001), while the "Traditional-inspired" DPP presented higher plant protein (p < 0.001) and fiber intakes (p < 0.001), and, therefore, a reduced carbohydrate-to-fiber quotient (p < 0.001). The "Med-fusion" DPP had the lowest protein-to-fat ratio (p < 0.001). Infants of women following the "Dairy-focused" DPP had the highest birth height centiles (p = 0.007) and the lowest ponderal index (p = 0.003). The NMR-metabolomics approach was implemented on a subset of women that provided amniotic fluid (AF) specimens (n = 62) to elucidate distinct metabolic signatures associated with DPPs. PCA and OPLS-DA models verified the adherence to three DPPs, revealing that the levels of several amino acids (AAs) were the highest in "Dairy-focused", reflecting its protein-rich nature. The "Traditional-inspired" DPP showed decreased AAs and glucose levels. This knowledge may contribute to optimizing maternal dietary recommendations. Further research is needed to validate these findings and better understand the relationships between maternal diet, AF metabolic signature, and neonatal anthropometrics.

Assessing Repeated Urinary Proline Betaine Measures as a Biomarker of Usual Citrus Intake during Pregnancy: Sources of Within-Person Variation and Correlation with Reported Intake

Proline betaine (Pro-B) has been identified as a biomarker of dietary citrus intake, yet gaps remain in its validation as a quantitative predictor of intake during various physiological states. This study quantified sources of within-individual variation (WIV) in urinary Pro-B concentration during pregnancy and assessed its correlation with the reported usual intake of citrus fruit and juice. Pro-B concentrations were determined by 1H-NMR spectroscopy in spot and 24-h urine specimens (n = 255) collected throughout pregnancy from women participating in the MARBLES cohort study. Adjusted linear or log mixed effects models quantified WIV and tested potential temporal predictors of continuous or elevated Pro-B concentration. Pearson or Spearman correlations assessed the relationship between averaged repeated biomarker measures and usual citrus intake reported by food frequency questionnaires. The proportion of variance in urinary Pro-B attributable to WIV ranged from 0.69 to 0.74 in unadjusted and adjusted models. Citrus season was a significant predictor of Pro-B in most analyses (e.g., adjusted β [95% CI]: 0.52 [0.16, 0.88] for non-normalized Pro-B), while gestational age predicted only non-normalized Pro-B (adjusted β [95% CI]: -0.093 [-0.18, -0.0038]). Moderate correlations (rs of 0.40 to 0.42) were found between reported usual citrus intake and averaged repeated biomarker measurements, which were stronger compared to using a single measurement. Given the high degree of WIV observed in urinary Pro-B, multiple samples per participant are likely needed to assess associations between citrus consumption and health outcomes.

Metabolic drivers of dysglycemia in pregnancy: ethnic-specific GWAS of 146 metabolites and 1-sample Mendelian randomization analyses in a UK multi-ethnic birth cohort

Introduction

Gestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and long-term health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). Recent evidence suggests that underlying metabolic difference contribute to this disparity, but an investigation of causality is required.

Methods

To address this, we paired metabolite and genomic data to evaluate the causal effect of 146 distinct metabolic characteristics on gestational dysglycemia in SAs and WEs. First, we performed 292 GWASs to identify ethnic-specific genetic variants associated with each metabolite (P ≤ 1 x 10-5) in the Born and Bradford cohort (3688 SA and 3354 WE women). Following this, a one-sample Mendelian Randomisation (MR) approach was applied for each metabolite against fasting glucose and 2-hr post glucose at 26-28 weeks gestation. Additional GWAS and MR on 22 composite measures of metabolite classes were also conducted.

Results

This study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Using MR approach, 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. Interestingly, in WEs, cholesterols were the dominant metabolite class driving with dysglycemia, while in SAs saturated fatty acids and total fatty acids were most commonly associated with dysglycemia.

Discussion

In summary, we confirm and demonstrate the presence of ethnic-specific causal relationships between metabolites and dysglycemia in mid-pregnancy in a UK population of SA and WE pregnant women. Future work will aim to investigate their biological mechanisms on dysglycemia and translating this work towards ethnically tailored GDM prevention strategies.

Early sex-dependent differences in metabolic profiles of overweight and adiposity in young children: a cross-sectional analysis

BACKGROUND

Childhood obesity is a global health concern and can lead to lifetime cardiometabolic disease. New advances in metabolomics can provide biochemical insights into the early development of obesity, so we aimed to characterize serum metabolites associated with overweight and adiposity in early childhood and to stratify associations by sex.

METHODS

Nontargeted metabolite profiling was conducted in the Canadian CHILD birth cohort (discovery cohort) at age 5 years (n = 900) by multisegment injection-capillary electrophoresis-mass spectrometry. Clinical outcome was defined using novel combined measures of overweight (WHO-standardized body mass index ≥ 85th percentile) and/or adiposity (waist circumference ≥ 90th percentile). Associations between circulating metabolites and child overweight/adiposity (binary and continuous outcomes) were determined by multivariable linear and logistic regression, adjusting for covariates and false discovery rate, and by subsequent sex-stratified analysis. Replication was assessed in an independent replication cohort called FAMILY at age 5 years (n = 456).

RESULTS

In the discovery cohort, each standard deviation (SD) increment of branched-chain and aromatic amino acids, glutamic acid, threonine, and oxoproline was associated with 20-28% increased odds of overweight/adiposity, whereas each SD increment of the glutamine/glutamic acid ratio was associated with 20% decreased odds. All associations were significant in females but not in males in sex-stratified analyses, except for oxoproline that was not significant in either subgroup. Similar outcomes were confirmed in the replication cohort, where associations of aromatic amino acids, leucine, glutamic acid, and the glutamine/glutamic acid ratio with childhood overweight/adiposity were independently replicated.

CONCLUSIONS

Our findings show the utility of combining measures of both overweight and adiposity in young children. Childhood overweight/adiposity at age 5 years has a specific serum metabolic phenotype, with the profile being more prominent in females compared to males.

Prepregnancy Body Mass Index and Lipoprotein Fractions are Associated with Changes in Women's Serum Metabolome from Late Pregnancy to the First Months of Postpartum

BACKGROUND

Pregnancy and postpartum are periods of intense changes in women's metabolism. The knowledge of the metabolites and maternal factors underlying these changes is limited.

OBJECTIVES

We aimed to investigate the maternal factors that could influence serum metabolome changes from late pregnancy to the first months of postpartum.

METHODS

Sixty-eight healthy women from a Brazilian prospective cohort were included. Maternal blood and general characteristics were collected during pregnancy (28-35 wk) and postpartum (27-45 d). A targeted metabolomics approach was applied to quantify 132 serum metabolites, including amino acids, biogenic amines, acylcarnitines, lysophosphatidylcholines (LPC), diacyl phosphatidylcholines (PC), alkyl:acyl phosphatidylcholines (PC-O), sphingomyelins with (SM) and without hydroxylation [SM(OH)], and hexoses. Metabolome changes from pregnancy to postpartum were measured as log₂ fold change (log₂FC), and simple linear regressions were employed to evaluate associations between maternal variables and metabolite log₂FC. Multiple comparison-adjusted P values of < 0.05 were considered significant.

RESULTS

Of 132 metabolites quantified in serum, 90 changed from pregnancy to postpartum. Most metabolites belonging to PC and PC-O classes decreased, whereas most LPC, acylcarnitines, biogenic amines, and a few amino acids increased in postpartum. Maternal prepregnancy body mass index (ppBMI) showed positive associations with leucine and proline. A clear opposite change pattern was observed for most metabolites across ppBMI categories. Few phosphatidylcholines were decreased in women with normal ppBMI, while an increase was observed in women with obesity. Similarly, women with high postpartum levels of total cholesterol, LDL cholesterol, and non-HDL cholesterol showed increased sphingomyelins, whereas a decrease was observed for women with lower levels of those lipoproteins.

CONCLUSIONS

The results revealed several maternal serum metabolomic changes from pregnancy to postpartum, and the maternal ppBMI and plasma lipoproteins were associated with these changes. We highlight the importance of the nutritional care of women prepregnancy to improve their metabolic risk profile.

Healthful eating patterns, serum metabolite profile and risk of diabetes in a population-based prospective study of US Hispanics/Latinos

AIMS/HYPOTHESIS

We aimed to evaluate associations of multiple recommended dietary patterns (i.e. the alternate Mediterranean diet [aMED], the Healthy Eating Index [HEI]-2015 and the healthful Plant-based Diet Index [hPDI]) with serum metabolite profile, and to examine dietary-pattern-associated metabolites in relation to incident diabetes.

METHODS

We included 2842 adult participants free from diabetes, CVD and cancer during baseline recruitment of the Hispanic Community Health Study/Study of Latinos. Metabolomics profiling of fasting serum was performed using an untargeted approach. Dietary pattern scores were derived using information collected by two 24 h dietary recalls. Dietary-pattern-associated metabolites were identified using multivariable survey linear regressions and their associations with incident diabetes were assessed using multivariable survey Poisson regressions with adjustment for traditional risk factors.

RESULTS

We identified eight metabolites (mannose, γ/β-tocopherol, N1-methylinosine, pyrraline and four amino acids) that were inversely associated with all dietary scores. These metabolites were detrimentally associated with various cardiometabolic risk traits, especially insulin resistance. A score comprised of these metabolites was associated with elevated risk of diabetes (RRper SD 1.54 [95% CI 1.29, 1.83]), and this detrimental association appeared to be attenuated or eliminated by having a higher score for aMED (pinteraction = 0.0001), HEI-2015 (pinteraction = 0.020) or hPDI (pinteraction = 0.023). For example, RR (95% CI) of diabetes for each SD increment in the metabolite score was 1.99 (1.44, 2.37), 1.67 (1.17, 2.38) and 1.08 (0.86, 1.34) across the lowest to the highest tertile of aMED score, respectively.

CONCLUSIONS/INTERPRETATION

Various recommended dietary patterns were inversely related to a group of metabolites that were associated with elevated risk of diabetes. Adhering to a healthful eating pattern may attenuate or eliminate the detrimental association between metabolically unhealthy serum metabolites and risk of diabetes.

Sources of Variation in Food-Related Metabolites during Pregnancy

The extent to which variation in food-related metabolites are attributable to non-dietary factors remains unclear, which may explain inconsistent food-metabolite associations observed in population studies. This study examined the association between non-dietary factors and the serum concentrations of food-related biomarkers and quantified the amount of variability in metabolite concentrations explained by non-dietary factors. Pregnant women (n = 600) from two Canadian birth cohorts completed a validated semi-quantitative food frequency questionnaire, and serum metabolites were measured by multisegment injection-capillary electrophoresis-mass spectrometry. Hierarchical linear modelling and principal component partial R-square (PC-PR2) were used for data analysis. For proline betaine and DHA (mainly exogenous), citrus foods and fish/fish oil intake, respectively, explained the highest proportion of variability relative to non-dietary factors. The unique contribution of dietary factors was similar (15:0, 17:0, hippuric acid, TMAO) or lower (14:0, tryptophan betaine, 3-methylhistidine, carnitine) compared to non-dietary factors (i.e., ethnicity, maternal age, gestational age, pre-pregnancy BMI, physical activity, and smoking) for metabolites that can either be produced endogenously, biotransformed by gut microbiota, and/or derived from multiple food sources. The results emphasize the importance of adjusting for non-dietary factors in future analyses to improve the accuracy and precision of the measures of food intake and their associations with health and disease.

Impact of Maternal Health Behaviours and Social Conditions on Infant Diet at Age 1-Year: Results from a Prospective Indigenous Birth Cohort in Ontario, Canada

Background: Understanding the impact of maternal health behaviours and social conditions on childhood nutrition is important to inform strategies to promote health during childhood. Objective: To describe how maternal health sociodemographic factors (e.g., socioeconomic status, education), health behaviours (e.g., diet), and traditional health care use during pregnancy impact infant diet at age 1-year. Methods: Data were collected from the Indigenous Birth Cohort (ABC) study, a prospective birth cohort formed in partnership with an Indigenous community-based Birthing Centre in southwestern Ontario, Canada. 110 mother-infant dyads are included in the study and were enrolled between 2012 and 2017. Multiple linear regression analyses were performed to understand factors associated with infant diet scores at age 1-year, with a higher score indicating a diet with more healthy foods. Results: The mean age of women enrolled during pregnancy was 27.3 (5.9) years. Eighty percent of mothers had low or moderate social disadvantage, 47.3% completed more than high school education, and 70% were cared for by a midwife during their pregnancy. The pre-pregnancy body mass index (BMI) was <25 in 34.5% of women, 15.5% of mothers smoked during pregnancy, and 14.5% of mothers had gestational diabetes. Being cared for by an Indigenous midwife was associated with a 0.9-point higher infant diet score (p = 0.001) at age 1-year, and lower maternal social disadvantage was associated with a 0.17-point higher infant diet quality score (p = 0.04). Conclusion: This study highlights the positive impact of health care provision by Indigenous midwives and confirms that higher maternal social advantage has a positive impact on child nutrition.

Serum metabolomic signatures of gestational diabetes in South Asian and white European women

INTRODUCTION

This study aimed to identify serum metabolomic signatures associated with gestational diabetes mellitus (GDM), and to examine if ethnic-specific differences exist between South Asian and white European women.

RESEARCH DESIGN AND METHODS

Prospective cohort study with a nested case-control analysis of 600 pregnant women from two Canadian birth cohorts; using an untargeted approach, 63 fasting serum metabolites were measured and analyzed using multisegment injection-capillary electrophoresis-mass spectrometry. Multivariate logistic regression modeling was conducted overall and by cohort.

RESULTS

The proportion of women with GDM was higher in South Asians (27.1%) compared with white Europeans (17.9%). Several amino acid, carbohydrate, and lipid pathways related to GDM were common to South Asian and white European women. Elevated circulating concentrations of glutamic acid, propionylcarnitine, tryptophan, arginine, 2-hydroxybutyric acid, 3-hydroxybutyric acid, and 3-methyl-2-oxovaleric acid were associated with higher odds of GDM, while higher glutamine, ornithine, oxoproline, cystine, glycine with lower odds of GDM. Per SD increase in glucose concentration, the odds of GDM increased (OR=2.07, 95% CI 1.58 to 2.71), similarly for metabolite ratios: glucose to glutamine (OR=2.15, 95% CI 1.65 to 2.80), glucose to creatinine (OR=1.79, 95% CI 1.39 to 2.32), and glutamic acid to glutamine (OR=1.46, 95% CI 1.16 to 1.83). South Asians had higher circulating ratios of glucose to glutamine, glucose to creatinine, arginine to ornithine, and citrulline to ornithine, compared with white Europeans.

CONCLUSIONS

We identified a panel of serum metabolites implicated in GDM pathophysiology, consistent in South Asian and white European women. The metabolic alterations leading to larger ratios of glucose to glutamine, glucose to creatinine, arginine to ornithine, and citrulline to ornithine in South Asians likely reflect the greater burden of GDM among South Asians compared with white Europeans.

Association between dietary choline and betaine intake and 10.6-year cardiovascular disease in adults

Background

Several studies have assessed the association between dietary choline and betaine and cardiovascular disease (CVD), but their results are inconsistent. The present study aimed to determine the association between dietary intake of choline and betaine and the risk of CVD in the general population over a 10.6-year period of follow-up.

Methods

The present cohort study was conducted on participants in the third wave of the Tehran Lipid and Glucose Study (2006–2008) and was followed-up until March 2018. Dietary intake of choline and betaine was calculated using the United States Department of Agriculture (USDA) database. Patients’ medical records were used to collect data on CVD.

Results

In this study, 2606 subjects with no previous CVD participated and were followed-up for a median of 10.6 years. During the follow-up periods, 187 incidences of CVD were detected. Results of the Cox proportional hazards regression indicated that neither energy-adjusted total choline nor betaine was associated with the incidence of CVD. Among individual choline forms, only higher intake of free choline (FC) was associated with a lower risk of CVD (HR: 0.64, 95% CI: 0.42–0.98). There was no significant association between each 10 mg/d increase in choline and betaine content of each food category and CVD.

Conclusion

Our investigation indicates no association between energy-adjusted total choline and betaine and a 10.6-year risk of CVD among adults. Besides, we found no relationship between individual choline forms (except FC) and CVD. We also found energy-adjusted choline and betaine obtained from food categories were not associated with the risk of CVD.

Non-esterified fatty acids as biomarkers of diet and glucose homeostasis in pregnancy: The impact of fatty acid reporting methods: NEFA reporting methods affect dietary and cardiometabolic endpoints

BACKGROUND

Sparse data exists on the utility of individual serum non-esterified fatty acids (NEFAs) as clinical and dietary biomarkers and how reporting methods could affect these associations. We investigated the associations of 19 serum NEFAs expressed as µM or mol%, with self-reported dietary intake data, and cardiometabolic health indicators in pregnant women.

METHODS

In this cross-sectional study, 273 pregnant women in their second trimester each completed a semi-quantitative food-frequency questionnaire and provided fasting serum samples. Comprehensive serum NEFA analysis was performed by multisegment injection-nonaqueous capillary electrophoresis-mass spectrometry. We evaluated the associations of NEFAs using two different reporting methods, with diet quality, specific foods intake, and measures of adiposity and glucose homeostasis.

RESULTS

Consistently stronger dietary correlations were observed when expressed as mol%. Serum ω-3 NEFAs were associated with diet quality and fish/fish oil daily servings (DHA mol%, r= 0.37; p = 4.8e-10), and odd-chain NEFAs were associated with full-fat dairy intake (15:0 mol%, r = 0.23; p = 9.0e-5). Glucose intolerance was positively associated with odd chain NEFAs as expressed in µM (r = 0.21; p= 0.001) but inversely associated when expressed as mol% (r = -0.31; p= 2.2e-7). In contrast, monounsaturated NEFAs (µM and mol%) had robust positive associations with pre-pregnancy BMI, second trimester skin-fold thickness, glycated hemoglobin, fasting glucose, and glucose intolerance.

CONCLUSIONS

This study demonstrates the utility of specific NEFAs and their sub-classes as viable dietary and clinical biomarkers when reported as their relative proportions. More research is needed to investigate inconsistencies between absolute concentrations and relative proportions when reporting fatty acids.

Metabolite profiles and the risk of metabolic syndrome in early childhood: a case-control study

BACKGROUND

Defining the metabolic syndrome (MetS) in children remains challenging. Furthermore, a dichotomous MetS diagnosis can limit the power to study associations. We sought to characterize the serum metabolite signature of the MetS in early childhood using high-throughput metabolomic technologies that allow comprehensive profiling of metabolic status from a biospecimen.

METHODS

In the Family Atherosclerosis Monitoring In earLY life (FAMILY) prospective birth cohort study, we selected 228 cases of MetS and 228 matched controls among children age 5 years. In addition, a continuous MetS risk score was calculated for all 456 participants. Comprehensive metabolite profiling was performed on fasting serum samples using multisegment injection-capillary electrophoresis-mass spectrometry. Multivariable regression models were applied to test metabolite associations with MetS adjusting for covariates of screen time, diet quality, physical activity, night sleep, socioeconomic status, age, and sex.

RESULTS

Compared to controls, thirteen serum metabolites were identified in MetS cases when using multivariable regression models, and using the quantitative MetS score, an additional eight metabolites were identified. These included metabolites associated with gluconeogenesis (glucose (odds ratio (OR) 1.55 [95% CI 1.25-1.93]) and glutamine/glutamate ratio (OR 0.82 [95% CI 0.67-1.00])) and the alanine-glucose cycle (alanine (OR 1.41 [95% CI 1.16-1.73])), amino acids metabolism (tyrosine (OR 1.33 [95% CI 1.10-1.63]), threonine (OR 1.24 [95% CI 1.02-1.51]), monomethylarginine (OR 1.33 [95% CI 1.09-1.64]) and lysine (OR 1.23 [95% CI 1.01-1.50])), tryptophan metabolism (tryptophan (OR 0.78 [95% CI 0.64-0.95])), and fatty acids metabolism (carnitine (OR 1.24 [95% CI 1.02-1.51])). The quantitative MetS risk score was more powerful than the dichotomous outcome in consistently detecting this metabolite signature.

CONCLUSIONS

A distinct metabolite signature of pediatric MetS is detectable in children as young as 5 years old and may improve risk assessment at early stages of development.

Association of Urinary and Plasma Levels of Trimethylamine N-Oxide (TMAO) with Foods

Introduction: Trimethylamine N-oxide (TMAO) may play a key mediator role in the relationship between the diet, gut microbiota and cardiovascular diseases, particularly in people with kidney failure. The aim of this review is to evaluate which foods have a greater influence on blood or urinary trimethylamine N-oxide (TMAO) levels. Methods: 391 language articles were screened, and 27 were analysed and summarized for this review, using the keywords “TMAO” AND “egg” OR “meat” OR “fish” OR “dairy” OR “vegetables” OR “fruit” OR “food” in December 2020. Results: A strong correlation between TMAO and fish consumption, mainly saltwater fish and shellfish, but not freshwater fish, has been demonstrated. Associations of the consumption of eggs, dairy and meat with TMAO are less clear and may depend on other factors such as microbiota or cooking methods. Plant-based foods do not seem to influence TMAO but have been less investigated. Discussion: Consumption of saltwater fish, dark meat fish and shellfish seems to be associated with an increase in urine or plasma TMAO values. Further studies are needed to understand the relationship between increased risk of cardiovascular disease and plasma levels of TMAO due to fish consumption. Interventions coupled with long-term dietary patterns targeting the gut microbiota seem promising.

The maternal serum metabolome by multisegment injection-capillary electrophoresis-mass spectrometry: a high-throughput platform and standardized data workflow for large-scale epidemiological studies

A standardized data workflow is described for large-scale serum metabolomic studies using multisegment injection-capillary electrophoresis-mass spectrometry. Multiplexed separations increase throughput (<4 min/sample) for quantitative determination of 66 polar/ionic metabolites in serum filtrates consistently detected (coefficient of variance (CV) <30%) with high frequency (>75%) from a multi-ethnic cohort of pregnant women (n = 1,004). We outline a validated protocol implemented in four batches over a 7-month period that includes details on preventive maintenance, sample workup, data preprocessing and metabolite authentication. We achieve stringent quality control (QC) and robust batch correction of long-term signal drift with good mutual agreement for a wide range of metabolites, including serum glucose as compared to a clinical chemistry analyzer (mean bias = 11%, n = 668). Control charts for a recovery standard (mean CV = 12%, n = 2,412) and serum metabolites in QC samples (median CV = 13%, n = 202) demonstrate acceptable intermediate precision with a median intraclass coefficient of 0.87. We also report reference intervals for 53 serum metabolites from a diverse population of women in their second trimester of pregnancy.