The protective associations of breastfeeding with infant overweight and asthma are not dependent on maternal FUT2 secretor status
Bibliographic record
Abstract
Breastfeeding supplies infant gut bacteria with human milk oligosaccharides (HMOs) as a nutrient source. HMO profiles are influenced by the FUT2 gene, which encodes an enzyme affecting the fucosylation of milk sugars. 20 to 40% of individuals have a “non-secretor” polymorphism that inactivates the FUT2 gene, resulting in variable HMO proportions in milk. This has engendered a concerning, yet unfounded, perception that non-secretor milk is “inferior.” To address this untested hypothesis, we re-analyzed two datasets in which we previously showed that breastfeeding was protective against early life asthma and excessive infant weight gain in the Canadian CHILD Cohort Study. Using stratified regression models, we found that the protective association of exclusive breastfeeding and infant asthma was not modified by maternal secretor status (secretors aOR: 0.53, 95% CI 0.31 to 0.92; non-secretors aOR: 0.36, 95% CI 0.12 to 1.04; p for interaction = 0.50, N = 2086 children). Similarly, the association of breastfeeding with lower infant BMI and weight gain velocity did not vary by maternal secretor status (infant BMI: secretors aβ −0.47, 95% CI −0.66 to −0.29; non-secretors aβ −0.46, 95% CI −0.78 to −0.13; p for interaction = 0.60; N = 1971 infants). Our results indicate that secretor and non-secretor mothers can equally promote infant growth and respiratory health through breastfeeding. These findings run contrary to the idea that non-secretor milk is an inferior food source, and instead reify the importance of breastfeeding for all infants. The results of this study can inform feeding recommendations that are applicable to all infants, regardless of maternal secretor status.
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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".