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Record W3007806060 · doi:10.1093/jcag/gwz047.222

A223 THE GEM PROJECT: ASSOCIATIONS OF DIETARY PATTERNS WITH MICROBIOME AND FECAL CALPROTECTIN IN HEALTHY FIRST-DEGREE RELATIVES OF CROHN’S DISEASE PATIENTS

2020· article· en· W3007806060 on OpenAlexaff
Gila Sasson, J Raygoza Garay, Williams Turpin, Namita Power, Michelle I. Smith, David S. Guttman, Ken Croitoru

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsMicrobiomeFecesCalprotectinBiologyGut floraDiseaseMediterranean dietGut microbiomeFirst-degree relativesImmunologyMedicinePhysiologyInflammatory bowel diseaseInternal medicineGeneticsEcologyFamily history

Abstract

fetched live from OpenAlex

Abstract Background Crohn’s disease (CD) is thought to be due to an interaction between environmental factors and the gut microbiome that activates an immune response in genetically susceptible hosts. Epidemiologic studies suggest diet is an important variable in CD development; however, little is known about the mechanism by which diet contributes to pathogenesis. It has recently been shown that diet plays a substantial role in shaping microbiome composition (MC). We hypothesize that specific diet patterns are associated with differences in MC that may be related to CD risk. Aims To characterize associations between diet patterns with MC and fecal calprotectin (FC) in healthy first-degree relatives (FDR’s) of CD patients in the Genetic, Environmental, Microbial (GEM) Project. Methods A validated food frequency questionnaire (FFQ) was used to assess diet for North American FDR’s at recruitment. Each question was summarized as a score based on weekly consumption frequency. The Dirichlet method of unsupervised clustering was used to generate dominant diet clusters. Diet-microbiome associations were assessed using the two-part microbiome model. Stool microbiota at recruitment was characterized by 16s RNA sequencing of V4 region using MiSeq platform. Baseline FC was measured by BUHLMANN ELISA test. Results 2766 FDR’s had FFQ’s at recruitment; mean age 18.52 years, 53% female. The Dirichlet method identified 4 clusters, some of which resembled known diet patterns: Superbowl (mainly organ meats, non-red meat, beer, spirits), High Carbohydrate (HC), Mediterranean (MD) and Western (WD) diets. HC was associated with increased relative abundance of V. veillonella (P=2.68E-4). Both HC and MD were associated with decreased abundance of E. klebsiella (P=2.64E-5 and P=1.02E-5 respectively). WD was associated with decreased abundance of L. dorea (P=5.74E-5), a genus considered high risk for CD. A per question analysis demonstrated significant associations between several taxa and individual foods. Diet clusters were then correlated with FC, and a decrease in FC was observed with MD (estimate -16.96, P=0.012). There were no associations with FC in a per question analysis. Conclusions Dominant dietary patterns and certain individual foods are associated with specific gut MC. As well, MD is inversely associated with FC and therefore has potential use as an intervention for lowering inflammation. Understanding relationships between diet, MC and FC in individuals at high risk for CD would be beneficial in defining new dietary strategies in predictably modulating future risk of CD. Funding Agencies CCCHelmsley Charitable Trust

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)0.002
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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".

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Citations2
Published2020
Admission routes1
Has abstractyes

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