The chromatin and single-cell transcriptional landscapes of CD4 T cells in inflammatory bowel disease link risk loci with a proinflammatory Th17 cell population
Bibliographic record
Abstract
Introduction: The imbalance between Th17 and regulatory T cells in inflammatory bowel diseases (IBD) promotes intestinal epithelial cell damage. In this scenario, T helper cell lineage commitment is accompanied by dynamic changes to the chromatin that facilitate or repress gene expression. Methods: Here, we characterized the chromatin landscape and heterogeneity of intestinal and peripheral CD4 T cellsfrom IBD patients using in house ATAC-Seq and single cell RNA-Seq libraries. Results: We show that chromatin accessibility profiles of CD4 T cells from inflamed intestinal biopsies relate to genes associated with a network of inflammatory processes. After integrating the chromatin profiles of tissue-derived CD4 T cells and in-vitro polarized CD4 T cell subpopulations, we found that the chromatin accessibility changes of CD4 T cells were associated with a higher predominance of pathogenic Th17 cells (pTh17 cells) in inflamed biopsies. In addition, IBD risk loci in CD4 T cells were colocalized with accessible chromatin changes near pTh17-related genes, as shown in intronic STAT3 and IL23R regions enriched in areas of active intestinal inflammation. Moreover, single cell RNA-Seq analysis revealed a population of pTh17 cells that co-expresses Th1 and cytotoxic transcriptional programs associated with IBD severity. Discussion: Altogether, we show that cytotoxic pTh17 cells were specifically associated with IBD genetic variants and linked to intestinal inflammation 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 | 0.000 | 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) | 0.002 | 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".