A collagen VI–dependent pathogenic mechanism for Hirschsprung’s disease
Bibliographic record
Abstract
Hirschsprung's disease (HSCR) is a severe congenital anomaly of the enteric nervous system (ENS) characterized by functional intestinal obstruction due to a lack of intrinsic innervation in the distal bowel. Distal innervation deficiency results from incomplete colonization of the bowel by enteric neural crest cells (eNCCs), the ENS precursors. Here, we report the generation of a mouse model for HSCR--named Holstein--that contains an untargeted transgenic insertion upstream of the collagen-6α4 (Col6a4) gene. This insertion induces eNCC-specific upregulation of Col6a4 expression that increases total collagen VI protein levels in the extracellular matrix (ECM) surrounding both the developing and the postnatal ENS. Increased collagen VI levels during development mainly result in slower migration of eNCCs. This appears to be due to the fact that collagen VI is a poor substratum for supporting eNCC migration and can even interfere with the migration-promoting effects of fibronectin. Importantly, for a majority of patients in a HSCR cohort, the myenteric ganglia from the ganglionated region are also specifically surrounded by abundant collagen VI microfibrils, an outcome accentuated by Down syndrome. Collectively, our data thus unveil a clinically relevant pathogenic mechanism for HSCR that involves cell-autonomous changes in ECM composition surrounding eNCCs. Moreover, as COL6A1 and COL6A2 are on human Chr.21q, this mechanism is highly relevant to the predisposition of patients with Down syndrome to HSCR.
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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) | 0.000 | 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) | 0.001 | 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".