Novel de novo mutations of the interleukin-10 receptor gene lead to infantile onset inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Defects in the interleukin 10 (IL-10) signalling pathway have been shown to cause very early onset inflammatory bowel disease (IBD). We report a patient with severe infantile-onset IBD with a compound heterozygous IL-10 receptor alpha subunit (IL-10RA) mutation, one of which was paternally-inherited and the other occurring de novo. METHODS: Deep sequencing of IL-10, IL-10RA and IL-10 receptor beta subunit (IL-10RB) were performed. Peripheral blood mononuclear cell (PBMC) surface expression of IL-10RA was analysed by flow cytometry. IL-10 signalling pathway was examined by measuring phosphorylated STAT3 in PBMC cultured in the presence of IL-6 or IL-10. RESULT: We identified a missense mutation in exon 4 of IL-10RA (c.583T>C) in one allele and a nonsense mutation in exon 7 of IL-10RA (c.1368G>T) in the other allele. Neither mutation has been reported previously. The patient has functional IL-10RA deficiency despite normal IL-10RA expression. CONCLUSION: This represents the first case report of a de novo mutation of IL-10RA that is associated with very early onset severe IBD. Therefore, IL-10 pathway defect should be considered in patients with infantile-onset IBD even if the parents are non-consanguineous.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.002 | 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".