Loss-of-function de novo mutations play an important role in severe human neural tube defects
Bibliographic record
Abstract
BACKGROUND: Neural tube defects (NTDs) are very common and severe birth defects that are caused by failure of neural tube closure and that have a complex aetiology. Anencephaly and spina bifida are severe NTDs that affect reproductive fitness and suggest a role for de novo mutations (DNMs) in their aetiology. METHODS: We used whole-exome sequencing in 43 sporadic cases affected with myelomeningocele or anencephaly and their unaffected parents to identify DNMs in their exomes. RESULTS: We identified 42 coding DNMs in 25 cases, of which 6 were loss of function (LoF) showing a higher rate of LoF DNM in our cohort compared with control cohorts. Notably, we identified two protein-truncating DNMs in two independent cases in SHROOM3, previously associated with NTDs only in animal models. We have demonstrated a significant enrichment of LoF DNMs in this gene in NTDs compared with the gene specific DNM rate and to the DNM rate estimated from control cohorts. We also identified one nonsense DNM in PAX3 and two potentially causative missense DNMs in GRHL3 and PTPRS. CONCLUSIONS: Our study demonstrates an important role of LoF DNMs in the development of NTDs and strongly implicates SHROOM3 in its aetiology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".