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Record W4391873622 · doi:10.1093/jcag/gwad061.301

A301 RELATIONSHIP BETWEEN INTRAHEPATIC IMMUNE CELL PROFILE AND MICROBIOME ACCORDING TO DISEASE SEVERITY IN OBESE PATIENTS WITH NON-ALCOHOLIC FATTY LIVER DISEASE

2024· article· en· W4391873622 on OpenAlexaff
Katherine J. P. Schwenger, Y Ghorbani, L Chen, Sandra E. Fischer, Timothy Jackson

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsFatty liverDiseaseGastroenterologyAlcoholic liver diseaseMedicineImmune systemInternal medicineMicrobiomeImmunologyCirrhosisBiologyBioinformatics

Abstract

fetched live from OpenAlex

Abstract Background Non-alcoholic fatty liver disease (NAFLD) includes histology ranging from simple steatosis (SS) to non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis. The pathogenesis of NAFLD is multifactorial and includes several immune cell-mediated inflammatory processes. Recent research suggests a potential relationship between NAFLD, disease severity and the intestinal microbiome (IM). In particular, our previous work in NAFLD showed that lower abundance of fecal Faecalibacterium prausnitzii was associated with liver histology and gene expression. In addition, we found that Kupffer cell markers, hematopoietic cell marker cluster of differentiation and B cells were associated with liver histology. Aims Knowing that F prausnitzii may have anti-inflammatory effect, we seek to determine if there was any association between fecal F prausnitzii and hepatic immune cells. Methods Biochemical and anthropometric measurements as well fecal samples for IM analysis were collected in those with obesity undergoing bariatric surgery. Fecal shotgun metagenome sequencing to profile the intestinal microbiome Liver histology was assessed using Brunt scoring system. The frequency, location and phenotype of 8 immune cell subtypes were analyzed by multiplex immunofluorescence. Spearman correlation coefficients and partial Spearman correlation coefficients were used to evaluate the association between significant hepatic immune cells and fecal F. prausnitzii. Results 113 patients had both hepatic immune and IM data. Of the 113 patients, 30 had normal liver obese (NLO), 41 had SS and 42 had NASH. With regards to hepatic immune cells, those with NAFLD (SS and NASH) or NASH had significantly higher Helper T, CD4 and B cells and lower activated macrophages compared to NLO. In those with NAFLD or NASH, F. prausnitzii was significantly negatively correlated with Helper T cells (NAFLD, R= -0.25, p-value 0.009; NASH, R= -0.25, p-value 0.038). In those with NASH, F. prausnitzii was also significantly negatively correlated with CD4 cells (R= -0.31, p-value 0.009). Conclusions Specific hepatic immune cells were associated with NAFLD and NASH with Helper T and CD4 cells being negatively correlated with F. prausnitzii. Knowing that these immune cells contribute to NAFLD pathogenesis, the relationship between fecal IM, hepatic immune cells and NAFLD require further exploration. Funding Agencies CIHRCanadian Liver Foundation

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 score0.005

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 head0.008
GPT teacher head0.221
Teacher spread0.214 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

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