Long ncRNA Landscape in the Ileum of Treatment-Naive Early-Onset Crohn Disease
Bibliographic record
Abstract
Background: Long noncoding RNAs (lncRNA) are key regulators of gene transcription and many show tissue-specific expression. We previously defined a novel inflammatory and metabolic ileal gene signature in treatment-naive pediatric Crohn disease (CD). We now extend our analyses to include potential regulatory lncRNA. Methods: Using RNAseq, we systematically profiled lncRNAs and protein-coding gene expression in 177 ileal biopsies. Co-expression analysis was used to identify functions and tissue-specific expression. RNA in situ hybridization was used to validate expression. Real-time polymerase chain reaction was used to test lncRNA regulation by IL-1β in Caco-2 enterocytes. Results: We characterize widespread dysregulation of 459 lncRNAs in the ileum of CD patients. Using only the lncRNA in discovery and independent validation cohorts showed patient classification as accurate as the protein-coding genes, linking lncRNA to CD pathogenesis. Co-expression and functional annotation enrichment analyses across several tissues and cell types 1showed that the upregulated LINC01272 is associated with a myeloid pro-inflammatory signature, whereas the downregulated HNF4A-AS1 exhibits association with an epithelial metabolic signature. We confirmed tissue-specific expression in biopsies using in situ hybridization, and validated regulation of prioritized lncRNA upon IL-1β exposure in differentiated Caco-2 cells. Finally, we identified significant correlations between LINC01272 and HNF4A-AS1 expression and more severe mucosal injury. Conclusions: We systematically define differentially expressed lncRNA in the ileum of newly diagnosed pediatric CD. We show lncRNA utility to correctly classify disease or healthy states and demonstrate their regulation in response to an inflammatory signal. These lncRNAs, after mechanistic exploration, may serve as potential new tissue-specific targets for RNA-based interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".