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Record W4388638540 · doi:10.1002/acn3.51944

Short‐chain fatty acid producers in the gut are associated with pediatric multiple sclerosis onset

2023· article· en· W4388638540 on OpenAlexafffundabout
Vinícius Andreoli Schoeps, Xiaoyuan Zhou, Mary Horton, Feng Zhu, Kathryn McCauley, Akash Virupakshaiah, Mark Gorman, Leslie Benson, Bianca Weinstock‐Guttman, Amy Waldman, Brenda Banwell, Amit Bar‐Or, Ruth Ann Marrie, Gary Van Domselaar, Julia O’Mahony, Ali Mirza, Çharles N. Bernstein, E. Ann Yeh, T. Charles Casper, Susan V. Lynch, Helen Tremlett, Sergio E. Baranzini, Emmanuelle Waubant

Bibliographic record

VenueAnnals of Clinical and Translational Neurology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSickKids FoundationUniversity of ManitobaUniversity of British Columbia
FundersNational Institute of Neurological Disorders and StrokeUniversity of TorontoMultiple Sclerosis SocietyEuropean Genomic Institute for DiabetesNational Multiple Sclerosis Society
KeywordsConfoundingMultiple sclerosisMicrobiomeMedicineLachnospiraceaeDiseaseObservational studyCase-control studyPhysiologyInternal medicineImmunologyBiologyBioinformaticsGeneGenetics

Abstract

fetched live from OpenAlex

OBJECTIVE: The relationship between multiple sclerosis and the gut microbiome has been supported by animal models in which commensal microbes are required for the development of experimental autoimmune encephalomyelitis. However, observational study findings in humans have only occasionally converged when comparing multiple sclerosis cases and controls which may in part reflect confounding by comorbidities and disease duration. The study of microbiome in pediatric-onset multiple sclerosis offers unique opportunities as it is closer to biological disease onset and minimizes confounding by comorbidities and environmental exposures. METHODS: A multicenter case-control study in which 35 pediatric-onset multiple sclerosis cases were 1:1 matched to healthy controls on age, sex, self-reported race, ethnicity, and recruiting site. Linear mixed effects models, weighted correlation network analyses, and PICRUSt2 were used to identify microbial co-occurrence networks and for predicting functional abundances based on marker gene sequences. RESULTS: Two microbial co-occurrence networks (one reaching significance after adjustment for multiple comparisons; q < 0.2) were identified, suggesting interdependent bacterial taxa that exhibited association with disease status. Both networks indicated a potentially protective effect of higher relative abundance of bacteria observed in these clusters. Functional predictions from the significant network suggested a contribution of short-chain fatty acid producers through anaerobic fermentation pathways in healthy controls. Consistent family-level findings from an independent Canadian-US study (19 case/control pairs) included Ruminococaccaeae and Lachnospiraceae (p < 0.05). Macronutrient intake was not significantly different between cases and controls, minimizing the potential for dietary confounding. INTERPRETATION: Our results suggest that short-chain fatty acid producers may be important contributors to multiple sclerosis onset.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.157
GPT teacher head0.365
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations7
Published2023
Admission routes3
Has abstractyes

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