The intestinal microbiome, but not clinical aspects of inflammatory bowel disease, is impacted by lactose malabsorption compared to lactose digestion in children
Bibliographic record
Abstract
BACKGROUND: Dietary exclusion of lactose from patients with inflammatory bowel disease (IBD) persists with speculation that deleterious effects are mediated through intestinal microbes. OBJECTIVES: To compare IBD characteristics and changes in the intestinal microbiome (IM) at diagnosis in children with and without lactose malabsorption (LM). METHODS: A cross-sectional cohort of children (8-17 y of age) diagnosed with Crohn's disease [n = 149 (63%)] or ulcerative colitis (n = 86) that had undergone lactose breath hydrogen testing was evaluated. The IM of mucosal luminal aspirates was profiled at the time of diagnosis using 16S ribosomal ribonucleic acid gene amplicon sequencing of the V6 hypervariable region. RESULTS: Of the 235 children, 61 (26%) had LM. Microbial characterization yielded differences in bacterial differential abundance between children who could and could not absorb lactose, which varied by intestinal site and between subtypes of IBD. There were no differences in the ages [13.2 ± 3.0 y (mean ± standard deviation) compared with 12.7 ± 3.4 y; P = 0.25], sex (P = 0.88), extent of disease involvement or severity of disease at presentation (P = 0.74) when comparing those that could or could not absorb lactose nor was there a difference in the need for initiation of biological agents (P = 0.43) during 2 y of follow-up. CONCLUSIONS: LM does not affect the clinical presentation or outcomes of children with IBD. However, this study establishes that a single nonabsorbed fermentable food product can alter the IM in both a regional and disease-specific manner. As we continue to learn more about the pathophysiology of IBD and the role of the IM in disease onset and progression, it would be of benefit to examine the impact of other potential fermentable nutrients and their products on IBD outcomes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".