Patient-derived organoid biobank identifies epigenetic dysregulation of intestinal epithelial MHC-I as a novel mechanism in severe Crohn’s Disease
Bibliographic record
Abstract
OBJECTIVE: Epigenetic mechanisms, including DNA methylation (DNAm), have been proposed to play a key role in Crohn's disease (CD) pathogenesis. However, the specific cell types and pathways affected as well as their potential impact on disease phenotype and outcome remain unknown. We set out to investigate the role of intestinal epithelial DNAm in CD pathogenesis. DESIGN: We generated 312 intestinal epithelial organoids (IEOs) from mucosal biopsies of 168 patients with CD (n=72), UC (n=23) and healthy controls (n=73). We performed genome-wide molecular profiling including DNAm, bulk as well as single-cell RNA sequencing. Organoids were subjected to gene editing and the functional consequences of DNAm changes evaluated using an organoid-lymphocyte coculture and a nucleotide-binding oligomerisation domain, leucine-rich repeat and CARD domain containing 5 (NLRC5) dextran sulphate sodium (DSS) colitis knock-out mouse model. RESULTS: and cognate gene upregulation. Single-cell RNA sequencing of primary mucosal tissue and IEOs confirmed the role of NLRC5 as transcriptional transactivator in the intestinal epithelium. Increased mucosal MHC-I and NLRC5 expression in adult and paediatric patients with CD was validated in additional cohorts and the functional role of MHC-I highlighted by demonstrating a relative protection from DSS-mediated mucosal inflammation in NLRC5-deficient mice. MHC-I DNAm in IEOs showed a significant correlation with CD disease phenotype and outcomes. Application of machine learning approaches enabled the development of a disease prognostic epigenetic molecular signature. CONCLUSIONS: Our study has identified epigenetically regulated intestinal epithelial MHC-I as a novel mechanism in CD pathogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".