The impact of human breast milk components on the infant metabolism
Bibliographic record
Abstract
BACKGROUND & AIMS: Breastfeeding is beneficial for mothers and infants. Underlying mechanisms and biochemical mediators thus need to be investigated to develop and support improved infant nutrition practices promoting the child health. We analysed the relation between maternal breast milk composition and infant metabolism. METHODS: 196 pairs of mothers and infants from a European research project (PreventCD) were studied. Maternal milk samples collected at month 1 and month 4 after birth were analysed for macronutrient classes, hormone, and fatty acid (FA) content. Phospholipids, acylcarnitines, and amino acids were measured in serum samples of 4-month old infants. Associations between milk components and infant metabolites were analysed with spearman correlation and linear mixed effect models (LME). P-values were corrected for multiple testing (PLME). RESULTS: Month 1 milk protein content was strongly associated with infant serum lyso-phosphatidylcholine (LPC) 14:0 (PLME = 0.009). Month 1 milk insulin was associated to infant acetylcarnitine (PLME = 0.01). There were no associations between milk protein content and serum amino acids and milk total fat content and serum polar lipids. Middle- and odd-chain FA% in breast milk at both ages were significantly related to serum LPC and sphingomyelins (SM) species in infant serum (all PLME<0.05), while FA% 20:5n-3 and 22:6n-3 percentages were significantly associated to serum LPC 22:6 (PLME = 1.91×10-4/7.93×10-5) in milk only at month 4. Other polyunsaturated fatty acids and hormones in milk showed only weak associations with infant serum metabolites. CONCLUSIONS: Infant serum LPC are influenced by breast milk FA composition and, intriguingly, milk protein content in early but not late lactation. LPC 14:0, previously found positively associated with obesity risk, was the serum metabolite which was the most strongly associated to milk protein content. Thus, LPC 14:0 might be a key metabolite not only reflecting milk protein intake in infants, but also relating high protein content in milk or infant formula to childhood obesity risk.
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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 | 0.001 | 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".