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Record W3177590516 · doi:10.1101/2021.07.05.451147

The relationship between mucosal microbiota, colitis and systemic inflammation in Chronic Granulomatous Disorder

2021· preprint· en· W3177590516 on OpenAlexfundno aff
Mehmet Davrandi, Stephanie Harris, Philip J Smith, Charles Murray, David M. Lowe

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2021
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
FundersUniversity College London Hospitals NHS Foundation TrustRare Disease FoundationBC Children's HospitalChildren's Hospital FoundationCSL Behring
KeywordsColitisMicrobiomePathogenesisImmunologyCalprotectinInflammationUlcerative colitisInflammatory bowel diseaseGut floraBacteroidesMedicineSystemic inflammationGastroenterologyInternal medicineBiologyDiseaseBioinformaticsBacteria

Abstract

fetched live from OpenAlex

Abstract Background Chronic granulomatous disorder (CGD) is a primary immunodeficiency which is frequently complicated by an inflammatory colitis and is associated with systemic inflammation. Objective To investigate the role of the microbiome in the pathogenesis of colitis and systemic inflammation. Methods We performed 16S rDNA sequencing on mucosal biopsy samples from each segment of 10 CGD patients’ colons, and conducted compositional and functional pathway prediction analyses. Results The microbiota in samples from colitis patients demonstrated reduced taxonomic alpha diversity compared to unaffected patients, even in apparently normal bowel segments. Functional pathway richness was similar between the colitic and non-colitic mucosa, although metabolic pathways involved in butyrate biosynthesis or utilisation were enriched in patients with colitis and correlated positively with faecal calprotectin levels. One patient with very severe colitis was dominated by Enterococcus spp., while among other patients Bacteroides spp. abundance correlated with colitis severity measured by faecal calprotectin and an endoscopic severity score. In contrast, Blautia abundance associated with low severity scores and mucosal health. Several taxa and functional pathways correlated with concentrations of inflammatory cytokines in blood but not with colitis severity. Notably, dividing patients into ‘High’ and ‘Low’ systemic inflammation groups demonstrated clearer separation than on the basis of colitis status in beta diversity analyses. Conclusion The microbiome is abnormal in CGD-associated colitis and altered functional characteristics probably contribute to pathogenesis. Furthermore, the relationship between the mucosal microbiome and systemic inflammation, independent of colitis status, implies that the microbiome in CGD can influence the inflammatory phenotype of the condition. Key Messages The colonic mucosal microbiome and bacterial metabolic pathways in patients with CGD colitis differ from patients without colitis, even in macroscopically normal bowel segments. The mucosal microbiome and bacterial metabolic pathways in patients with CGD also differ according to the extent of systemic inflammation, independently from the presence of colitis, suggesting a role for the gut microbiota in the inflammatory phenotype of this condition. Capsule summary The pathogenesis of chronic granulomatous disorder (CGD)-associated colitis and other inflammatory complications is unclear. We demonstrate potentially treatable alterations in the mucosa-associated microbiome in CGD colitis and microbial differences which associate with systemic inflammation independently of colitis status.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.231
Teacher spread0.221 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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