Mediterranean diet and associations with the gut microbiota and pediatric-onset multiple sclerosis using trivariate analysis
Bibliographic record
Abstract
BACKGROUND: The interplay between diet and the gut microbiota in multiple sclerosis (MS) is poorly understood. We aimed to assess the interrelationship between diet, the gut microbiota, and MS. METHODS: We conducted a case-control study including 95 participants (44 pediatric-onset MS cases, 51 unaffected controls) enrolled from the Canadian Pediatric Demyelinating Disease Network study. All had completed a food frequency questionnaire ≤21-years of age, and 59 also provided a stool sample. RESULTS: Here we show that a 1-point increase in a Mediterranean diet score is associated with 37% reduced MS odds (95%CI: 10%-53%). Higher fiber and iron intakes are also associated with reduced MS odds. Diet, not MS, explains inter-individual gut microbiota variation. Several gut microbes abundances are associated with both the Mediterranean diet score and having MS, and these microbes are potential mediators of the protective associations of a healthier diet. CONCLUSIONS: Our findings suggest that the potential interaction between diet and the gut microbiota is relevant in MS.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".