Investigation of metabolomic biomarkers for childhood executive function and the role of genetic and dietary factors: The GUSTO cohort
Bibliographic record
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".