Intestinal epithelial vitamin D receptor deletion leads to defective autophagy in colitis
Bibliographic record
Abstract
OBJECTIVE: Vitamin D and the vitamin D receptor (VDR) appear to be important immunological regulators of inflammatory bowel diseases (IBD). Defective autophagy has also been implicated in IBD, where interestingly, polymorphisms of genes such as ATG16L1 have been associated with increased risk. Although vitamin D, the microbiome and autophagy are all involved in pathogenesis of IBD, it remains unclear whether these processes are related or function independently. DESIGN: We investigated the effects and mechanisms of intestinal epithelial VDR in healthy and inflamed states using cell culture models, a conditional VDR knockout mouse model (VDR(ΔIEC)), colitis models and human samples. RESULTS: Absence of intestinal epithelial VDR affects microbial assemblage and increases susceptibility to dextran sulfate sodium-induced colitis. Intestinal epithelial VDR downregulates expressions of ATG16L1 and lysozyme, and impairs antimicrobial function of Paneth cells. Gain and loss-of-function assays showed that VDR levels regulate ATG16L1 and lysozyme at the transcriptional and translational levels. Moreover, low levels of intestinal epithelial VDR correlated with reduced ATG16L1 and representation by intestinal Bacteroides in patients with IBD. Administration of the butyrate (a fermentation product of gut microbes) increases intestinal VDR expression and suppresses inflammation in a colitis model. CONCLUSIONS: Our study demonstrates fundamental relationship between VDR, autophagy and gut microbial assemblage that is essential for maintaining intestinal homeostasis, but also in contributing to the pathophysiology of IBD. These insights can be leveraged to define therapeutic targets for restoring VDR expression and function.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".