Early-life gut microbiome is associated with behavioral disorders in the Rio birth cohort
Bibliographic record
Abstract
Emerging evidence has been linking changes in the early-life gut microbiome and neurodevelopmental outcomes. The founder bacteria that first colonize the infant’s gut determine the microbial succession that signals host tissues and impact development including the brain. Here we investigated the association between the meconium microbiome and neurobehavior. To this end, we surveyed the 16S rRNA gene on meconium samples and assessed behavioral outcomes at six-months of age by the Denver Developmental Screening Test II (DDST-II). Among the four behavioral domains investigated, the personal-social domain was associated with significant differences in meconium bacterial beta diversity (unweighted UniFrac; R 2 0.078, p = 0.021) and reduced alpha diversity (β = −2.290, 95% CI = −4.212; CI = −0.368), after adjustment for gestational antibiotics, preterm delivery, and delivery mode. Besides, this altered neurobehavior (failing to meet the milestone) was associated with overrepresented Ruminococcaceae, Christensenellaceae, and Eubacterium , Treponema , Senegalimassilia , Ruminiclostridium , Roseburia , Romboutsia , Prevotella , and Veillonella seminalis. Predicted functional genes showed reduced abundance in association with altered neurobehavior (all q < 0.15). Fine and gross motor skills presented no associations with the microbiome. This pilot study shows associations between the first gut microbiome and behavioral outcomes that deserve further studies in different neonate populations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".