Differential miRNA Expression in Ileal and Colonic Tissues Reveals an Altered Immunoregulatory Molecular Profile in Individuals With Crohn’s Disease versus Healthy Subjects
Bibliographic record
Abstract
BACKGROUND: MicroRNAs [miRNAs] are key modulators of gene expression in Crohn's disease [CD] and may drive tissue-specific molecular alterations underlying CD susceptibility. In this study, we analysed differential miRNA expression between CD and healthy subjects across ileal and colonic tissues. METHODS: A cohort of CD and healthy control [HC] subjects was recruited and clinical data collected. Endoscopically quiescent CD [CDq] was defined as inactive or mild by the Simple Endoscopic Score for CD. Total RNA was extracted from endoscopic biopsies taken from the terminal ileum and sigmoid colon. miRNA expression was quantified using NanoString Technologies. Statistical significance was assessed across biopsy site and diagnosis per miRNA, and corrected for multiple testing. RESULTS: In total, 23 CDq and 38 HC subjects were enrolled; 112 samples were included in the analysis, 51 from the ileum and 61 from the colon. We found 47 miRNAs differentially expressed by biopsy site in healthy tissue. Nine miRNAs were differentially expressed across HC and CDq, accounting for biopsy location. One of these, miR-223-3p, showed age and sex effects. We identified miRNA expression driven by diagnosis targeting genes involved in chemokine and cytokine signalling. miR-31-5p expression was driven by location and may be a biomarker for location subtypes in CD. CONCLUSIONS: We identified differentially expressed miRNAs in healthy ileal and colonic tissues. We discovered spatial miRNA expression patterns in CD and HC, suggesting site-specific regulation in subjects with no or minimal intestinal inflammation. These miRNAs target genes involved in immunoregulatory processes, suggesting a functional, tissue-specific role in CD.
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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 | 0.001 |
| 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".