Infant gut microbiota and food sensitization: associations in the first year of life
Bibliographic record
Abstract
BACKGROUND: The gut microbiota is established during infancy and plays a fundamental role in shaping host immunity. Colonization patterns may influence the development of atopic disease, but existing evidence is limited and conflicting. OBJECTIVE: To explore associations of infant gut microbiota and food sensitization. METHODS: Food sensitization at 1 year was determined by skin prick testing in 166 infants from the population-based Canadian Healthy Infant Longitudinal Development (CHILD) study. Faecal samples were collected at 3 and 12 months, and microbiota was characterized by Illumina 16S rRNA sequencing. RESULTS: Twelve infants (7.2%) were sensitized to ≥ 1 common food allergen at 1 year. Enterobacteriaceae were overrepresented and Bacteroidaceae were underrepresented in the gut microbiota of food-sensitized infants at 3 months and 1 year, whereas lower microbiota richness was evident only at 3 months. Each quartile increase in richness at 3 months was associated with a 55% reduction in risk for food sensitization by 1 year (adjusted odds ratio 0.45, 95% confidence interval 0.23-0.87). Independently, each quartile increase in Enterobacteriaceae/Bacteroidaceae ratio was associated with a twofold increase in risk (2.02, 1.07-3.80). These associations were upheld in a sensitivity analysis among infants who were vaginally delivered, exclusively breastfed and unexposed to antibiotics. At 1 year, the Enterobacteriaceae/Bacteroidaceae ratio remained elevated among sensitized infants, who also tended to have decreased abundance of Ruminococcaceae. CONCLUSIONS AND CLINICAL RELEVANCE: Low gut microbiota richness and an elevated Enterobacteriaceae/Bacteroidaceae ratio in early infancy are associated with subsequent food sensitization, suggesting that early gut colonization may contribute to the development of atopic disease, including food allergy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".