Abstract Background Trimethylamine N-oxide (TMAO) is a microbiome- and diet-derived metabolite implicated in adverse cardiovascular outcomes. To date, studies of plasma TMAO concentrations have largely focused on individuals with metabolic disease. As such, data on TMAO concentrations in population settings and parent–child dyads are lacking. Objectives This study aimed to investigate parent–child concordance, age, and sex effects on plasma concentrations of TMAO and its precursors [l-carnitine, choline, betaine, and dimethylglycine (DMG)]. Associations between concentrations of TMAO and its precursors and self-reported dietary intakes of animal protein (i.e., red meat, meat products, chicken, fish, milk products, and cheese) and fast-food meals were also investigated. Methods A total of 1166 children (mean ± SD age: 11 ± 0.5 y, 51% female) and 1324 parents (mean ± SD age: 44 ± 5.1 y, 87% female) had a biomedical assessment as part of Growing Up in Australia's Child Health Checkpoint. Plasma TMAO and precursor concentrations were quantified using ultra-high-pressure LC coupled with tandem MS. Results Familial dyads significantly contributed to plasma TMAO and precursor concentrations (P < 0.0001), explaining 37% of variance for TMAO concentrations. Least-square mean ± SE plasma TMAO was lower in children (0.79 ± 0.02 µM on the log-scale) than in adults (1.22 ± 0.02 µM). By contrast, children's betaine (40.30 ± 0.34 µM) and DMG concentrations (1.02 ± 0.01 µM on the log-scale) were higher than adults’ betaine (37.50 ± 0.32 µM) and DMG concentrations (0.80 ± 0.01 µM) (P < 0.0001). Mean values of all metabolites, except adult TMAO, were higher in males than in females (P < 0.001). Greater reported intake of red meat and fish was associated with higher TMAO concentrations in both children [estimates (95% CIs) for red meat: 0.06 (0.01, 0.10); fish: 0.11 (0.06, 0.17)] and adults [red meat: 0.13 (0.08, 0.17); meat products: 0.07 (0.03, 0.12); and fish: 0.09 (0.04, 0.14)]. Conclusions Age, sex, and shared family factors, including diet, contribute to variation in plasma concentrations of TMAO and its precursors.

Amino acid (AA) concentrations are influenced by both exogenous (e.g. diet, lifestyle) and endogenous factors (e.g. genetic, transcriptomic, epigenetic, and metabolomic). Fasting plasma AA profiles in adulthood are predictive of diabetes risk over periods of up to 12 years. Data on AA profiles in cross-generational cohorts, including individuals from shared gene-environment settings are scarce, but would allow the identification of the contribution of heritable and environmental factors characterising the levels of circulating AAs. This study aimed to investigate parent–child (familial dyad) concordance, absolute differences between generations- (children versus adults), age- (in adults: 28–71 years), and sex-dependent differences in plasma AA concentrations. Plasma AA concentrations were measured by UHPLC/MS–MS in 1166 children [mean (SD) age 11 (0.5) years, 51% female] and 1324 of their parents [44 (5.1) years, 87% female]. AA concentrations were variably concordant between parents and their children (5–41% of variability explained). Most AA concentrations were higher in adults than children, except for the non-essential AAs arginine, aspartic acid, glutamine, hydroxy-proline, proline, and serine. Male adults and children typically had higher AA concentrations than females. The exceptions were alanine, glutamine, glycine, hydroxy-proline, serine, and threonine in girls; and glycine and serine in women. Age, sex, and shared familial factors are important determinants of plasma AA concentrations.

Epidemiological studies have consistently demonstrated that environmental exposures in early life are associated with later-life health status and disease susceptibility. Epigenetic modifications, such as DNA methylation, have been suggested as potential mechanisms linking the intrauterine environment with offspring health status. The present systematic review compiles peer-reviewed randomized controlled trials assessing the impact of maternal nutritional interventions on DNA methylation patterns of the offspring. The results of the included trials are consistent with micronutrient supplementation not significantly affecting offspring tissue DNA methylation patterns, yet subgrouping by sex, BMI, and smoking status increased the significance of nutritional supplementation on DNA methylation. Maternal BMI and smoking status as well as offspring sex were factors influencing offspring DNA methylation responsiveness to nutritional interventions during pregnancy. Future research should aim at assessing the impact of nutritional interventions on DNA methylation patterns of neonates comparing single versus multi-micronutrient supplementation, within populations having high versus low baseline nutritional statuses.

Background Trimethylamine N-oxide (TMAO) is a diet- and microbiome-derived metabolite and a proposed biomarker of adverse cardiometabolic outcomes. TMAO studies have mainly been conducted in individuals with cardiometabolic disease, and studies in population-derived samples are limited. Objective We aimed to investigate the associations between plasma TMAO concentrations and its precursors [carnitine, choline, betaine, and dimethylglycine (DMG)] with metabolic syndrome (MetS) scores, preclinical cardiovascular phenotypes, and inflammatory biomarkers (i.e. high-sensitivity C-reactive protein and serum glycoprotein acetyls) in a population-derived cohort of children and their parents. Methods The concentrations of TMAO and its precursors were quantified using UHPLC coupled with tandem MS (UHPLC/MS-MS) in 1166 children (mean age 11 y ± 0.5 y, 51% female) and 1324 adults (44 y ± 5.1 y, 87% female) participating in The Growing Up in Australia's Child Health CheckPoint Study. We developed multivariable fractional polynomial models to analyze associations between TMAO, its precursors, MetS (adjusted for sex and age), and cardiovascular phenotypes (adjusted for sex, age, BMI, household income, and the urinary albumin to creatinine ratio). Pearson's correlations were computed to identify associations between TMAO, its precursors, and inflammatory biomarkers. Results The concentrations of TMAO precursors, but not TMAO itself, were associated with MetS, cardiovascular phenotypes, and inflammatory biomarkers in children and adults. Conclusions TMAO precursors, but not TMAO itself, were associated with adverse cardiometabolic and inflammatory phenotypes in children and adults. TMAO precursor concentrations may better reflect cardiovascular health and inflammatory status within the wider population. Replication in other population settings and mechanistic studies are warranted.

Diet and lifestyle are vital to population health, but their true contribution is difficult to quantify using traditional methods. Nutrient–health relations are typically based on epidemiological associations that are assessed at the population level, traditionally using self-reported dietary and lifestyle data. Unfortunately, such measures are inherently inaccurate. New technologies such as metabolomics can measure nutritional and micronutrient profiles in body fluids, providing objective evaluation of nutritional status. A critical step toward accurate health prediction models would be the building of integrated repositories of nutritional measures combining subjective methods of reporting with objective metabolomics profiles and precise phenotypic data. Here we outline a roadmap to achieve this goal and discuss both the advantages and risks of this approach. We also highlight the uncertain associations between the complexity of high-dimensional data generated in ‘omics research (along with the public confusion this may engender) and the rapid adoption of ‘omics approaches by nutrition and health companies to develop nutritional products and services.