Associations Between Immune Markers and Gut Microbiota in Pediatric Multiple Sclerosis and Controls (S29.008)
Bibliographic record
Abstract
Background/objective: Little is known about the association(s) between gut microbiota profiles and host immunological markers; we explored these in children with and without multiple sclerosis (MS). Methods: Children ≤18 years old attending a UCSF pediatric clinic provided stool and blood samples. MS cases were within 2 years of onset. Controls were free from autoimmune disorders (asthma and eczema allowed). The 16S rRNA gene was amplified from extracted DNA and bacterial profiles were generated using QIIME (Quantitative Insights Into Microbial Ecology). Peripheral blood mononuclear cells were isolated, and Treg (CD4+CD25+CD127lowFoxP3+) frequency and intracellular cytokine production (IFN-γ, IL-17A, IL-4, IL-10) by CD4 T cells were evaluated by flow cytometry. These immune markers were compared between cases and controls and associations with the gut microbiota explored. Results: Twenty-four children (15 relapsing-remitting MS cases, 9 controls) with a mean age of 12.6 years (SD=4.18; range 4-18) were included; 9/24 (38[percnt]) were boys. The mean MS disease duration was 10.0 months; 7 were disease-modifying drug exposed. Although immune markers (e.g. IFN-g, IL-17, IL-10, CD4+CD25+Foxp3+ Treg) did not differ between groups (all p>0.05), divergence between cases and controls in the associations with the gut microbiota and host immunological markers were observed. IL-17+ T cells were positively associated with overall richness and evenness for cases (r=0.665, p=0.018 and r=0.545, p=0.067, respectively), but not controls (r=-0.644, p=0.061 and r=-0.728, p=0.026, respectively). At the phylum level, IL-17 T-cells were inversely associated with Bacteroidetes abundance for cases (r=-0.719, p=0.008) but not controls (r=0.320, p=0.401). Conversely, Tregs ([percnt] CD4+) significantly correlated with Fusobacteria for controls (r=0.817, p=0.007), but not cases (r=0.129, p=0.646 ). Conclusions: Associations were found between gut microbiota and host immunological (blood) markers which differed for children with and without MS. Further work is needed to validate and explore these divergent findings and understand their potential role 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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".