Infants born to mothers with IBD present with altered gut microbiome that transfers abnormalities of the adaptive immune system to germ-free mice
Bibliographic record
Abstract
Background and aims Prenatal and early life bacterial colonisation is thought to play a major role in shaping the immune system. Furthermore, accumulating evidence links early life exposures to the risk of developing IBD later in life. We aimed to assess the effect of maternal IBD on the composition of the microbiome during pregnancy and on the offspring’s microbiome. Methods We prospectively examined the diversity and taxonomy of the microbiome of pregnant women with and without IBD and their babies at multiple time points. We evaluated the role of maternal IBD diagnosis, the mode of delivery, antibiotic use and feeding behaviour on the microbiome composition during early life. To assess the effects of IBD-associated maternal and infant microbiota on the enteric immune system, we inoculated germ-free mice (GFM) with the respective stool and profiled adaptive and innate immune cell populations in the murine intestines. Results Pregnant women with IBD and their offspring presented with lower bacterial diversity and altered bacterial composition compared with control women and their babies. Maternal IBD was the main predictor of the microbiota diversity in the infant gut at 7, 14, 30, 60 and 90 days of life. Babies born to mothers with IBD demonstrated enrichment in Gammaproteobacteria and depletion in Bifidobacteria . Finally, GFM inoculated with third trimester IBD mother and 90-day infant stools showed significantly reduced microbial diversity and fewer class-switched memory B cells and regulatory T cells in the colon. Conclusion Aberrant gut microbiota composition persists during pregnancy with IBD and alters the bacterial diversity and abundance in the infant stool. The dysbiotic microbiota triggered abnormal imprinting of the intestinal immune system in GFM.
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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".