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Record W4200274519 · doi:10.1002/acn3.51476

The gut microbiota in pediatric multiple sclerosis and demyelinating syndromes

2021· article· en· W4200274519 on OpenAlexaffabout
Helen Tremlett, Feng Zhu, Douglas L. Arnold, Amit Bar‐Or, Çharles N. Bernstein, Christine Bonner, Jessica D. Forbes, Morag Graham, Janace Hart, Natalie Knox, Ruth Ann Marrie, Ali Mirza, Julia O’Mahony, Gary Van Domselaar, E. Ann Yeh, Yinshan Zhao, Brenda Banwell, Emmanuelle Waubant

Bibliographic record

VenueAnnals of Clinical and Translational Neurology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsManitoba HealthPublic Health Agency of CanadaUniversity of ManitobaSickKids FoundationUniversity of TorontoMontreal Neurological Institute and HospitalMcGill UniversityHospital for Sick ChildrenUniversity of British Columbia
Fundersnot available
KeywordsLachnospiraceaeMultiple sclerosisMedicineAmplicon sequencingInternal medicineClinically isolated syndromeGastroenterologyMicrobiomeGut floraImmunologyBiologyBioinformatics16S ribosomal RNAGeneticsGeneFirmicutes

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.122
GPT teacher head0.369
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations68
Published2021
Admission routes2
Has abstractyes

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