Review article: biological mechanisms for symptom causation by individual FODMAP subgroups ‐ the case for a more personalised approach to dietary restriction
Bibliographic record
Abstract
BACKGROUND: Due to the paucity of targeted therapy for irritable bowel syndrome (IBS), many patients turn to dietary modifications for symptom management. The combination of five subgroups of poorly absorbed and rapidly fermented carbohydrates-fructans, galacto-oligosaccharides, lactose, excess fructose and polyols-are thought to trigger gastrointestinal symptoms and are referred to collectively as "FODMAPs". AIMS: To examine the biological plausibility and mechanisms by which foods high in specific FODMAP subgroups cause symptoms, and to use this information to explore the possibility of targeting select dietary components to allow for a more personalised approach to dietary adjustment METHODS: Recent literature was analysed via search databases including Medline, PubMed and Scopus. RESULTS: Lactose, fructans and galacto-oligosaccharides have strong biologic plausibility for symptom generation due to lack of hydrolases resulting in distention from osmosis and rapid fermentation. However, excess fructose and polyols may only cause symptoms in specific individuals when consumed in high doses, but this remains to be established. There is evidence to suggest that certain patient characteristics such as ethnicity may predict response to lactose, but differentiation of other subgroups is difficult prior to dietary manipulation. CONCLUSIONS: While some clear mechanisms of action for symptom generation have been established, further research is needed to understand which patients will respond to specific FODMAP subgroup restriction. We suggest that clinicians consider in some patients a tailored, personalised "bottom-up" approach to the low-FODMAP diet, such as dietary restriction relevant to the patients' ethnicity, symptom profile and usual dietary intake.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".