Plasma metabolomic profile of adiposity and body composition in childhood: The Genetics of Glucose regulation in Gestation and Growth cohort
Bibliographic record
Abstract
Summary Objective This study identified metabolite modules associated with adiposity and body fat distribution in childhood using gold‐standard measurements. Methods We used cross‐sectional data from 329 children at mid‐childhood (age 5.3 ± 0.3 years; BMI 15.7 ± 1.5 kg/m 2 ) from the Genetics of Glucose regulation in Gestation and Growth (Gen3G), a prospective pre‐birth cohort. We quantified 1038 plasma metabolites and measured body composition using the gold‐standard dual‐energy x‐ray absorptiometry (DXA), in addition to skinfold, waist circumference, and BMI. We applied weighted‐correlation network analysis to identify a network of highly correlated metabolite modules. Spearman's partial correlations were applied to determine the associations of adiposity with metabolite modules and individual metabolites with false discovery rate (FDR) correction. Results We identified a ‘green’ module of 120 metabolites, primarily comprised of lipids (mostly sphingomyelins and phosphatidylcholine), that showed positive correlations (all FDR p < 0.05) with DXA estimates of total and truncal fat ( ρ adjusted = 0.11–0.19), skinfold measures ( ρ adjusted = 0.09–0.26), and BMI and waist circumference ( ρ adjusted = 0.15 and 0.18, respectively). These correlations were similar when stratified by sex. Within this module, sphingomyelin (d18:2/14:0, d18:1/14:1)*, a sphingomyelin sub‐specie that is an important component of cell membranes, showed the strongest associations. Conclusions A module of metabolites was associated with adiposity measures in childhood.
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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".