Combined Histo-endoscopic Remission but not Endoscopic Healing Alone in Ulcerative Colitis is Associated with a Mucosal Transcriptional Profile Resembling Healthy Mucosa
Bibliographic record
Abstract
BACKGROUND AND AIMS: A composite endpoint of histological and endoscopic remission is proposed to be the most complete measure of mucosal healing in ulcerative colitis [UC]. We aim to establish the prognosis, and transcriptional and microbial features of histo-endoscopic remission and activity. METHODS: A cross-sectional endoscopic rectosigmoid colon sample collection from UC patients and healthy controls [HC] was performed for histopathology and host genome-wide RNA-sequencing. Histo-endoscopic remission and histo-endoscopic activity were defined as Mayo endoscopic subscore [MES] 0-1 with and without histological activity, respectively. UC relapse, defined as symptomatic and endoscopic worsening, was retrospectively recorded for survival analysis. Unsupervised and differential gene expression analyses were performed, and the interaction between transcriptomics and mucosal gut microbiota was analysed based on the 16S rRNA gene sequencing profile. RESULTS: UC patients with histo-endoscopic remission showed a significantly lower risk of relapse compared to histo-endoscopic activity. Unsupervised analysis of the transcriptomic profile showed that histo-endoscopic remission and histo-endoscopic activity samples clustered with HC and MES 2-3 samples, respectively. A total of 452 host genes enriched for humoral immune response, antimicrobial defence, chemokine and TH17 signalling pathway were upregulated in histo-endoscopic activity compared to histo-endoscopic remission. A set of host genes with antimicrobial properties showed significant associations with mucosal microbiota. CONCLUSIONS: The rectosigmoid mucosa transcriptional profile of UC patients in histo-endoscopic remission resembles that of HC mucosa and confers a lower risk of relapse. These data support that the combination of histo-endoscopic remission could be the most appropriate definition of mucosal healing in UC.
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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 | 0.000 | 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".