P841 Evaluation of gut microbiota composition in NAFLD with UC pancolitis in clinical remission: a pilot study
Bibliographic record
Abstract
Abstract Background Non-alcoholic fatty liver disease (NAFLD) is the main cause of liver disease in Western countries and is a frequently reported comorbidity in inflammatory bowel disease (IBD). A complex interaction among polygenic predisposition, IBD-specific risk factors, microbiome, multiple environmental and patients’ factors could explain the development of NAFLD in IBD. Gut dysbiosis is increasingly recognised as an important player in NAFLD, as well as in IBD pathogenesis. So far, no study has examined the gut microbiota composition in IBD patients with NAFLD. We aimed to characterise faecal microbiota according to NAFLD status in a pilot cohort of ulcerative colitis (UC) pancolitis in clinical remission. Methods This was a cross-sectional pilot study using transient elastography (TE) with controlled attenuation parameter (CAP) to diagnose NAFLD in UC pancolitis patients in clinical remission, defined as partial Mayo score ≤1. NAFLD was diagnosed non-invasively as CAP ≥248 dB/m. Exclusion criteria included: use of corticosteroids in the last year and antibiotics or probiotics/prebiotics in the last 2 months prior to inclusion; significant alcohol intake (AUDIT-C <5); hepatitis B or C infection. Stool samples were collected within 12 h from TE with CAP evaluation. Gut microbiota composition was analysed by 16S rRNA gene sequencing with Illumina technique. Statistical analysis by NAFLD status was performed using Fisher’s exact or Mann–Whitney’s test as appropriate. Results A total of 11 UC pancolitis patients in clinical remission were included (mean age 53 years, 36.4% male, time since IBD diagnosis 16 years). NAFLD was diagnosed in 7 cases (63.6%, mean CAP 291 dB/m). Patients with pancolitis and NAFLD had higher BMI (mean 31 vs. 22 kg/m2, p = 0.006) as well as waist circumference (mean 100 vs. 81 cm, p = 0.006) compared with those without NAFLD, but no other differences in demographic, clinical or pharmacological parameters were found between pancolitis with or without NAFLD. Patients with pancolitis and NAFLD clustered separately from those without NAFLD, when computing Bray Curtis dissimilarities (tested with Adonis, p = 0.006). In addition, patients with pancolitis and NAFLD presented with decreased bacterial richness (p = 0.017) but not diversity. This was accompanied by a significant increase of Bacteroides spp. relative abundance in faecal samples of patients with pancolitis and NAFLD (q = 0.017). Conclusion This pilot study demonstrates, for the first time, that, in UC pancolitis patients, NAFLD associates with altered gut microbiota composition. Further studies are needed to understand the exact role of gut microbiota in UC pancolitis with NAFLD and to evaluate the use of microbiota-directed approaches for the treatment of NAFLD in these patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".