Early Changes in Microbial Community Structure Are Associated with Sustained Remission After Nutritional Treatment of Pediatric Crohnʼs Disease
Bibliographic record
Abstract
BACKGROUND: Clinical remission achieved by exclusive enteral nutrition (EEN) is associated with marked microbiome changes. In this prospective study of exclusive enteral nutrition, we employ a hierarchical model of microbial community structure to distinguish between pediatric Crohn's disease patients who achieved sustained remission (SR) and those who relapsed early (non-SR), after restarting a normal diet. METHODS: Fecal samples were obtained from 10 patients (age 10-16) and from 5 healthy controls (age 9-14). The microbiota was assessed via 16S rRNA sequencing. In addition to standard measures of microbial biodiversity, we employed Bayesian methods to characterize the hierarchical community structure. Community structure between patients who sustained remission (wPCDAI <12.5) up to their 24-week follow-up (SR) was compared with patients that had not sustained remission (non-SR). RESULTS: Microbial diversity was lower in Crohn's disease patients relative to controls and lowest in patients who did not achieve SR. SR patients differed from non-SR patients in terms of the structure and prevalence of their microbial communities. The SR prevalent community contained a number of strains of Akkermansia muciniphila and Bacteroides and was limited in Proteobacteria, whereas the non-SR prevalent community had a large Proteobacteria component. Their communities were so different that a model trained to discriminate SR and non-SR had 80% classification accuracy, already at baseline sampling. CONCLUSIONS: Microbial community structure differs between healthy controls, patients who have an enduring response to exclusive enteral nutrition, and those who relapse early on introduction of normal diet. Our novel Bayesian approach to these differences is able to predict sustained remission after exclusive enteral nutrition.
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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".