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Record W4252676402 · doi:10.1093/jcag/gwab002.028

A29 NOVEL FECAL BIOMARKERS THAT PRECEDE CLINICAL DIAGNOSIS OF ULCERATIVE COLITIS

2021· article· en· W4252676402 on OpenAlexaff
Heather J. Galipeau, A Caminero Fernandez, Williams Turpin, Miriam Bermúdez-Brito, Alba Santiago, Josie Libertucci, Marco Constante, J Raygoza Garay, Gaston Rueda, Alexandra Clarizio, M I Smith, Matthew D. Surette, Přemysl Berčík, K Croitoru, Elena F. Verdú

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of TorontoMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsUlcerative colitisFecesInflammatory bowel diseaseMetagenomicsUniFracBiologyGastroenterologyGut floraDysbiosisInternal medicineCalprotectinImmunologyDiseaseMedicineMicrobiology16S ribosomal RNAGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Background Altered gut microbiota composition and function has been associated with inflammatory bowel diseases (IBD) including ulcerative colitis (UC), but causality and mechanisms remain unknown. Most studies have examined patients with active or treated disease and little is known about microbial compositional or functional changes that occur before disease onset. Aims We studied a longitudinal cohort of subjects at risk for IBD to define the fecal microbial composition and function in subjects prior to UC onset (pre-UC) and at diagnosis (post-UC), and in matched at-risk subjects that remained healthy. Methods Fecal samples were collected from healthy individuals at-risk for IBD (pre-UC; n=13) and subjects were followed longitudinally until UC diagnosis (post-UC, n=9), at which point another fecal sample was collected. Fecal samples from a cohort of matched at-risk individuals that did not develop UC were used as healthy controls (n=48). We applied 16S rRNA gene sequencing, next generation shotgun sequencing, in vitro proteolytic assays and gnotobiotic colonizations to define the microbial composition and proteolytic function in fecal samples. Results The microbiota of post-UC subjects clustered separately from pre-UC and HC subjects, based on bray-curtis and unweighted UniFrac, had reduced alpha-diversity, and had reduced abundance of Aldercreutzia compared to pre-UC and HC. In vitro functional analysis revealed increased fecal proteolytic and elastase activity in pre-UC and post-UC samples compared to HC. Metagenomics identified pathways and gene families related to protein metabolism and proteases/peptides that were significantly different between HC and pre-UC samples, suggesting a bacterial component to the pre-UC proteolytic signature. Elastase activity inversely correlated with the relative abundance of Adlercreutzia, and other potentially beneficial taxa, and directly correlated with Bacteroides vulgatus, a known proteolytic taxon. High elastase activity was confirmed in Bacteroides isolates from fecal samples. Bacterial contribution and functional significance of the proteolytic signature was investigated in germ-free adults and litters born from dams colonized with HC, pre-UC or post-UC microbiota. Mice colonized with pre-UC microbiota at adulthood or neonatally developed higher fecal proteolytic activity and an inflammatory immune tone compared with HC colonized mice. Conclusions We have identified increased fecal proteolytic activity that precedes clinical diagnosis of UC and associates with gut microbiota changes. This may constitute a non-invasive biomarker of inflammation to monitor at-risk populations that can be targeted therapeutically with anti-proteases. Funding Agencies CAG, CCC, CIHR

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)0.001
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.283
Teacher spread0.264 · 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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