Dietary Intake Is Unlikely to Explain Symptom Severity and Syndrome-Specific Microbiome Alterations in a Cohort of Women with Fibromyalgia
Bibliographic record
Abstract
BACKGROUND: Significant alterations were recently identified in the composition and putative function of the gut microbiome in women with fibromyalgia. As diet can influence the composition of the gut microbiome, differences in nutritional intake could, in theory, account for some of these specific fibromyalgia microbiome alterations. The current study aims to compare the diet of women with fibromyalgia to that of controls in order to explore possible associations between the intake of certain nutrients, symptom severity and gut microbiome composition. METHODS: The study population was comprised of 56 women with fibromyalgia and 68 controls. Dietary intake was assessed using the NIH Automated Self-Administered 24 h recall, following dietitian's instructions and the completion of a three-day dietary recall. The gut microbiome was assessed by 16S ribosomal RNA gene sequencing of stool samples. RESULTS: Most demographic and anthropometric characteristics were comparable between groups. The average energy and macronutrient intake (total and relative) and overall diet quality score were not different between patients and controls, nor were the main vitamins, minerals, fatty acids, alcohol, caffeine, sugar or fiber intakes. The daily intake of micronutrients and normalized macronutrients in women with fibromyalgia was largely not correlated with disease-specific measures, including pain intensity, fatigue, cognitive symptoms and quality of sleep, or with the relative quantity of almost any of the gut microbiome bacterial taxa differentially abundant in fibromyalgia. CONCLUSION: These data demonstrate that dietary intakes, as evaluated by self-reported questionnaires, probably cannot explain the syndrome-specific differences in gut microbiome or the clinical phenotype of fibromyalgia.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".