Investigation of metabolomic biomarkers for childhood executive function and the role of genetic and dietary factors: The GUSTO cohort

Abstract

Background: Few studies have investigated molecular biomarkers of specific executive function (EF) skills in children. We aimed to characterise the prospective associations between metabolome and multiple domains of EF using a bidirectional design.

Methods: This study was conducted within a longitudinal birth cohort, the Growing Up in Singapore Towards healthy Outcomes (GUSTO). Circulating levels of 165 metabolites were quantified using a nuclear magnetic resonance based metabolomics platform (n = 457 (∼6yrs) and n = 524 (∼8yrs)). Parent-reported EF was available for 495 children (∼7yrs). Multivariate linear regression was used to assess the metabolite-EF relationships. We examined the role of body composition, dietary factors, and genetics in the metabolite-EF associations.

Findings: Higher leucine level (∼6yrs) was associated with poorer EF (∼7yrs, Initiate (P = 0.003) and Working Memory (P = 0.004)). EF (∼7yrs) was not associated with leucine (∼8yrs). Importantly, we found weak evidence for associations of dietary factors (∼5yrs) with leucine (∼6yrs) and EF (∼7yrs). Each copy of C allele in rs1260326 (a leucine-related polymorphism) was associated with higher leucine level and poorer Initiate and Working Memory (P < 0.05). Amongst those with less strongly genetically influenced leucine, inverse association between leucine and cognitive regulation were weaker among those with higher BMI.

Interpretation: The observed association between higher leucine level and poorer EF may be determined by genetics and may not be easily amenable to dietary interventions. Further research is needed for validation and to understand mechanisms.

Funding: Singapore National Research Foundation and Agency for Science, Technology and Research.

Keywords: Dietary factor; Executive function; Genetic; Metabolite.

Figure 1

Study design and data availability a) Flowchart for study sample from the Growing Up in Singapore Towards healthy Outcomes (GUSTO) prospective study and sample sizes for data collected at various time points; b) Venn diagram indicating overlapping sample sizes between different domains of data. Dietary factors in b-3 represents individuals with assessment from either food frequency questionnaire (FFQ) or energy consumption tasks.

Figure 2

Network illustration for association analyses between metabolites and executive function (Metab.yr6→EF.yr7 and EF.yr7→Metab.yr8). Edges indicate associations with nominal P-value < 0.01. Edge colours indicate direction of associations (Green: positive associations. Pink: inverse associations). Node colours indicate different groups of metabolites or EF scales (Green: cognitive regulation. Pink: behavioural regulation. Purple: emotional regulation). Model 1 adjusted for age at blood draw for metabolite measurement, age at executive function assessment, and sex (n = 277∼348). Model 2 is Model 1 additionally adjusted for maternal ethnicity, maternal educational level, and household income at recruitment (n = 262∼327). Model 3 is Model 2 additionally adjusted for child body-mass index (BMI) at the time of exposure measurement (n = 262∼321). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Figure 3

Longitudinal associations of branched-chain amino acids (BCAAs) at age 6 years with executive function (cognitive regulation index) at age 7 years stratified by genotype of rs1260326. Beta indicates the change in executive function T-Score per standard deviation higher of natural log-transformed BCAAs. Model adjusted for age, sex, maternal ethnicity, maternal educational level, household income, body-mass index (BMI) at age 6 years. Sample sizes are 103, 109, and 35 for CC, CT, and TT genotype, respectively. Larger shapes indicate associations that the 95% confidence interval did not cover the null value. Red shapes indicate associations with a P-value smaller than 0.017 (i.e., 0.05/(3 genotype groups)). (Leucine (Leu), isoleucine (Ile), valine (Val)).

Figure 4

Regression-based causal mediation analysis for Leu (yr6; Above median vs Below median) → BMI (yr6) → Cognitive regulation T-Scores (yr7). Pure natural indirect effect is the effect of exposure on outcome due to the mediation only. The difference between the total natural indirect effect and the pure natural indirect effect indicates the effect due to interaction. (Leucine (Leu), body-mass index (BMI), Cognitive Regulation Index (CRI); total effect=pure natural direct effect + total natural indirect effect = pure natural indirect effect + total natural direct effect; larger shapes indicate associations that the 95% confidence interval did not cover the null value).