Fish-oil supplementation in pregnancy, child metabolomics and asthma risk
Bibliographic record
Abstract
BACKGROUND: We recently demonstrated that maternal dietary supplementation with fish oil-derived n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFAs) during pregnancy reduces the risk of asthma in the offspring but the mechanisms involved are unknown. METHODS: Here we investigated potential metabolic mechanisms using untargeted liquid chromatography-mass spectrometry-based metabolomics on 577 plasma samples collected at age 6 months in the offspring of mothers participating in the n-3 LCPUFA randomized controlled trial. First, associations between the n-3 LCPUFA supplementation groups and child metabolite levels were investigated using univariate regression models and data-driven partial least square discriminant analyses (PLS-DA). Second, we analyzed the association between the n-3 LCPUFA metabolomic profile and asthma development using Cox-regression. Third, we conducted mediation analyses to investigate whether the protective effect of n-3 LCPUFA on asthma was mediated via the metabolome. FINDINGS: The univariate analyses and the PLS-DA showed that maternal fish oil supplementation affected the child's metabolome, especially with lower levels of the n-6 LCPUFA pathway-related metabolites and saturated and monounsaturated long-chain fatty acids-containing compounds, lower levels of metabolites of the tryptophan pathway, and higher levels of metabolites in the tyrosine and glutamic acid pathway. This fish oil-related metabolic profile at age 6 months was significantly associated with a reduced risk of asthma by age 5 and the metabolic profile explained 24% of the observed asthma-protective effect in the mediation analysis. INTERPRETATION: Several of the observed pathways may be involved in the asthma-protective effect of maternal n-3 LCPUFA supplementation and act as mediators between the intervention and disease development. FUNDING: COPSAC is funded by private and public research funds all listed on www.copsac.com.
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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".