Integrative Analysis of Colonic Biopsies from Inflammatory Bowel Disease Patients Identifies an Interaction Between Microbial Bile Acid-inducible Gene Abundance and Human Angiopoietin-like 4 Gene Expression
Bibliographic record
Abstract
BACKGROUND AND AIMS: Microbial-derived bile acids can modulate host gene expression, and their faecal abundance is decreased in active inflammatory bowel disease [IBD]. We analysed the impact of endoscopic inflammation on microbial genes involved in bile acid biotransformation, and their interaction with host transcriptome in the intestinal mucosa of IBD patients. METHODS: Endoscopic mucosal biopsies were collected from non-inflamed and inflamed terminal ileum, ascending and sigmoid colon of IBD patients. Prediction of imputed metagenome functional content from 16S rRNA profile and real-time quantitative polymerase chain reaction [qPCR] were utsed to assess microbial bile acid biotransformation gene abundance, and RNA-seq was used for host transcriptome analysis. Linear regression and partial Spearman correlation accounting for age, sex, and IBD type were used to assess the association between microbial genes, inflammation, and host transcriptomics in each biopsy location. A Bayesian network [BN] analysis was fitted to infer the direction of interactions between IBD traits and microbial and host genes. RESULTS: The inferred microbial gene pathway involved in secondary bile acid biosynthesis [ko00121 pathway] was depleted in inflamed terminal ileum of IBD patients compared with non-inflamed tissue. In non-inflamed sigmoid colon, the relative abundance of bile acid-inducible [baiCD] microbial genes was positively correlated with the host Angiopoietin-like 4 [Angptl4] gene expression. The BN analysis suggests that the microbial baiCD gene abundance could affect Angptl4 expression, and this interaction appears to be lost in the presence of inflammation. CONCLUSIONS: Endoscopic inflammation affects the abundance of crucial microbial bile acid-metabolising genes and their interaction with Angptl4 in intestinal mucosa of IBD 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".