Genome-Wide Copy Number Analysis Uncovers a New HSCR Gene: NRG3
Bibliographic record
Abstract
Hirschsprung disease (HSCR) is a congenital disorder characterized by aganglionosis of the distal intestine. To assess the contribution of copy number variants (CNVs) to HSCR, we analysed the data generated from our previous genome-wide association study on HSCR patients, whereby we identified NRG1 as a new HSCR susceptibility locus. Analysis of 129 Chinese patients and 331 ethnically matched controls showed that HSCR patients have a greater burden of rare CNVs (p = 1.50 × 10(-5)), particularly for those encompassing genes (p = 5.00 × 10(-6)). Our study identified 246 rare-genic CNVs exclusive to patients. Among those, we detected a NRG3 deletion (p = 1.64 × 10(-3)). Subsequent follow-up (96 additional patients and 220 controls) on NRG3 revealed 9 deletions (combined p = 3.36 × 10(-5)) and 2 de novo duplications among patients and two deletions among controls. Importantly, NRG3 is a paralog of NRG1. Stratification of patients by presence/absence of HSCR-associated syndromes showed that while syndromic-HSCR patients carried significantly longer CNVs than the non-syndromic or controls (p = 1.50 × 10(-5)), non-syndromic patients were enriched in CNV number when compared to controls (p = 4.00 × 10(-6)) or the syndromic counterpart. Our results suggest a role for NRG3 in HSCR etiology and provide insights into the relative contribution of structural variants in both syndromic and non-syndromic HSCR. This would be the first genome-wide catalog of copy number variants identified in 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".