The gut microbiota in pediatric multiple sclerosis and demyelinating syndromes
Bibliographic record
Abstract
Abstract Objective To examine the gut microbiota in individuals with and without pediatric‐onset multiple sclerosis (MS). Methods We compared stool‐derived microbiota of Canadian Pediatric Demyelinating Disease Network study participants ≤21 years old, with MS (disease‐modifying drug [DMD] exposed and naïve) or monophasic acquired demyelinating syndrome [monoADS] (symptom onset <18 years), and unaffected controls. All were ≥30 days without antibiotics or corticosteroids. V4 region 16S RNA gene‐derived amplicon sequence variants (Illumina MiSeq) were assessed using negative binomial regression and network analyses; rate ratios were age‐ and sex‐adjusted (aRR). Results Thirty‐two MS, 41 monoADS (symptom onset [mean] = 14.0 and 6.9 years) and 36 control participants were included; 75%/56%/58% were female, with mean ages at stool sample = 16.5/13.8/15.1 years, respectively. Nine MS cases (28%) were DMD‐naïve. Although microbiota diversity (alpha, beta) did not differ between participants ( p > 0.1), taxa‐level and gut community networks did. MS (vs. monoADS) exhibited > fourfold higher relative abundance of the superphylum Patescibacteria (aRR = 4.2;95%CI:1.6–11.2, p = 0.004, Q = 0.01), and lower abundances of short‐chain fatty acid (SCFA)‐producing Lachnospiraceae ( Anaerosporobacter ) and Ruminococcaceae ( p , Q < 0.05). DMD‐naïve MS cases were depleted for Clostridiales vadin‐BB60 (unnamed species) versus either DMD‐exposed, controls ( p , Q < 0.01), or monoADS ( p = 0.001, Q = 0.06) and exhibited altered community connectedness ( p < 10 −9 Kruskal–Wallis), with SCFA‐producing taxa underrepresented. Consistent taxa‐level findings from an independent US Network of Pediatric MS Centers case/control ( n = 51/42) cohort included >eightfold higher abundance for Candidatus Stoquefichus and Tyzzerella (aRR = 8.8–12.8, p < 0.05) in MS cases and 72%–80% lower abundance of SCFA‐producing Ruminococcaceae‐NK4A214 (aRR = 0.38–0.2, p ≤ 0.01). Interpretation Gut microbiota community structure, function and connectivity, and not just individual taxa, are of likely importance 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".