Metabolomics: population epidemiology and concordance in Australian children aged 11–12 years and their parents

Abstract

ObjectivesNuclear magnetic resonance (NMR) metabolomics is high throughput and cost-effective, with the potential to improve the understanding of disease and risk. We examine the circulating metabolic profile by quantitative NMR metabolomics of a sample of Australian 11–12 year olds children and their parents, describe differences by age and sex, and explore the correlation of metabolites in parent–child dyads.DesignThe population-based cross-sectional Child Health CheckPoint study nested within the Longitudinal Study of Australian Children.SettingBlood samples collected from CheckPoint participants at assessment centres in seven Australian cities and eight regional towns; February 2015–March 2016.Participants1180 children and 1325 parents provided a blood sample and had metabolomics data available. This included 1133 parent–child dyads (518 mother–daughter, 469 mother–son, 68 father–daughter and 78 father–son).Outcome measures228 metabolic measures were obtained for each participant. We focused on 74 biomarkers including amino acid species, lipoprotein subclass measures, lipids, fatty acids, measures related to fatty acid saturation, and composite markers of inflammation and energy homeostasis.ResultsWe identified differences in the concentration of specific metabolites between childhood and adulthood and in metabolic profiles in children and adults by sex. In general, metabolite concentrations were higher in adults than children and sex differences were larger in adults than in children. Positive correlations were observed for the majority of metabolites including isoleucine (CC 0.33, 95% CI 0.27 to 0.38), total cholesterol (CC 0.30, 95% CI 0.24 to 0.35) and omega 6 fatty acids (CC 0.28, 95% CI 0.23 to 0.34) in parent–child comparisons.ConclusionsWe describe the serum metabolite profiles from mid-childhood and adulthood in a population-based sample, together with a parent–child concordance. Differences in profiles by age and sex were observed. These data will be informative for investigation of the childhood origins of adult non-communicable diseases and for comparative studies in other populations.

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

“…A large familial resemblance in metabolite concentrations has been suggested, which seems to be largely genetic (Draisma et al 2013;Kettunen et al 2016;Rueedi et al 2014). In cross-sectional studies, correlations of metabolites between parents and their offspring vary strongly, ranging from weak to relatively strong (Ellul et al 2019;Halvorsen et al 2015;Ohlund et al 2011). Partly in line with these previous studies, we observed that AA and NEFA concentrations were lower in childhood as compared to cord blood samples, whereas concentrations of PL and Carn were higher in childhood.…”

“…Differences in these factors between mothers and their children and over time might explain the weak correlations between different time points. Previous studies observed sex differences in metabolite concentrations in both children and adults (Ellul et al 2019;Teodoro-Morrison et al 2015). We did not observe metabolite concentrations to vary between the sexes.…”

“…Correlations of 0-0.29, 0.3-0.49, 0.5-0.69, 0.7-0.89, and 0.9-1.0 were considered to be very low, low, moderate, high and very high, respectively (Hinkle et al 2003). As sex differences in metabolite concentrations may exist (Ellul et al 2019), we repeated steps one and three stratified by child's sex. The statistical analyses were performed using R version 3.3.4 (R Foundation for Statistical Computing) (R Core Team 2015).…”

“…We did not observe metabolite concentrations to vary between the sexes. This could be explained by the relatively young age of the participants, as sex differences in metabolite concentrations have been shown to be more pronounced in adolescence and adulthood (Ellul et al 2019;Teodoro-Morrison et al 2015). Thus, correlations between individual metabolites between pregnant women and their children at school-age and within children over time are very low.…”

Current Status of Metabolomic Biomarker Discovery: Impact of Study Design and Demographic Characteristics

“…Major challenges exist translating metabolomic biomarkers from discovery to application in population health studies that characterize human biology focused on systemic metabolism [2][3][4][32][33][34][35]. Wide chemical diversity and the presence of isomers and isobaric compounds prevent a single bioanalytical platform from providing all-inclusive discovery of metabolites in a biological system.…”