IL23R (Interleukin 23 Receptor) Variants Protective against Inflammatory Bowel Diseases (IBD) Display Loss of Function due to Impaired Protein Stability and Intracellular Trafficking
Bibliographic record
Abstract
Genome-wide association studies as well as murine models have shown that the interleukin 23 receptor (IL23R) pathway plays a pivotal role in chronic inflammatory diseases such as Crohn disease (CD), ulcerative colitis, psoriasis, and type 1 diabetes. Genome-wide association studies and targeted re-sequencing studies have revealed the presence of multiple potentially causal variants of the IL23R. Specifically the G149R, V362I, and R381Q IL23Rα chain variants are linked to protection against the development of Crohn disease and ulcerative colitis in humans. Moreover, the exact mechanism of action of these receptor variants has not been elucidated. We show that all three of these IL23Rα variants cause a reduction in IL23 receptor activation-mediated phosphorylation of the signal-transducing activator of transcription 3 (STAT3) and phosphorylation of signal transducing activator of transcription 4 (STAT4). The reduction in signaling is due to lower levels of cell surface receptor expression. For G149R, the receptor retention in the endoplasmic reticulum is due to an impairment of receptor maturation, whereas the R381Q and V362I variants have reduced protein stability. Finally, we demonstrate that the endogenous expression of IL23Rα protein from V362I and R381Q variants in human lymphoblastoid cell lines exhibited lower expression levels relative to susceptibility alleles. Our results suggest a convergent cause of IL23Rα variant protection against chronic inflammatory disease.
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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) | 0.003 | 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".