MétaCan
Menu
Back to cohort
Record W4206912025 · doi:10.1093/ecco-jcc/jjab232.833

P712 Fungal microbiota composition in Inflammatory Bowel Disease patients in a Norwegian cohort: characterization of disease phenotypes and correlation with clinical activity and disease course

2022· article· en· W4206912025 on OpenAlexaboutno aff
Ignacio Catalán‐Serra, Silje Thorsvik, Vidar Beisvåg, Torunn Bruland, David M. Underhill, Arne K. Sandvik, Atle van Beelen Granlund

Bibliographic record

VenueJournal of Crohn s and Colitis · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
Fundersnot available
KeywordsInflammatory bowel diseaseGut floraBiologyDiseaseMedicineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background There is growing evidence of the role of the fungal microbiota in the pathogenesis of IBD, but a definite pattern defining the mycobiome in IBD is currently lacking. In addition, the variations within the different phenotypes as well as the correlation between fungal composition and disease outcomes has been poorly characterized. Our aim is to evaluate the fungal composition within the different IBD phenotypes, the changes with disease activity and the association with disease outcomes. Methods This prospective study presents sequencing of the faecal fungi of 111 individuals: 89 IBD (52 UC/37 CD) and 22 HC. Demographics,medication,Montreal Classification and disease history was collected. A fCalpro>100 was considered active disease. A subset of IBD patients was followed clinically (6±2 y) and classified as either “Complicated” or “Uncomplicated” based on the need of intensified medication and/or surgery. Sequencing was done on amplicons targeting the ITS1 region of fungal DNA on a Illumina MiSeq sequencer. Chosen OTUs were compiled taxonomically.Data analysis was performed in R(phyloseq and deSeq2-packages). Results We found significant variations in the fungal microbiota composition in the different IBD phenotypes(Fig1) In UC, Saccharomyces was predominant in pancolitis (E3), while Penicillium was more abundant in proctitis(E1) and Galactomyces in left-side UC (E2)(Pan.A). At species level, Rhodotorula mucilaginosa was significantly depleted in E3 (p≤0.05)(Pan.B) In CD, Aspergillus was predominant in ileal affection(L1) while Candida and Rhodotorula genus were more abundant in L2-L3.Patients with structuring phenotype(B2) were depleted of Apergillus and Rodhotorula (Pan.A). At species level, ileal (L1) patients were depleted of Candida tropicalis and Penicillium kudriavzevii. B1 patients had a marked predominance of Candida albicans vs B2(p≤0.01)(Pan.B) The mycobiome correlation with disease activity is depicted (Pan.C). Candida dublinensis was overrepresented in activity, while Saccharomyces pastorianus was depleted(p≤0.01) The correlation of the mycobiome with disease outcomes is represented in Pan.D. Penicillium glabrum was significantly overrepresented in patients with a complicated course. The abundance of Candida tropicalis and D. nepalensis was correlated with the need for surgery. Conclusion This study shows important differences in the fungal microbiota composition in the different IBD phenotypes. Some species are clearly correlated with the activity of the disease and worse clinical outcomes suggesting a potential deleterious role.Candida tropicalis was associated with the need of surgery in CD. This in-depth characterization of the mycobiome serves as a significant addition to the understanding of the role of fungi in IBD.

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)0.001
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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.239
Teacher spread0.235 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Crohn s and ColitisSame topicGut microbiota and healthFrench-language works237,207