Whole exome sequencing identifies novel predisposing genes in neural tube defects
Bibliographic record
Abstract
BACKGROUND: Neural tube defects (NTD) are among the most common defects affecting 1:1000 births. They are caused by a failure of neural tube closure during development. Their clinical presentation is diverse and dependent on the site and severity of the original defect on the embryonic axis. The etiology of NTD is multifactorial involving environmental factors and genetic variants that remain largely unknown. METHODS: We have conducted a whole exome sequencing (WES) study in five new NTD families and pooled the results with WES data from three NTD families and 43 trios that were previously investigated by our group. We analyzed the data using biased candidate gene and unbiased gene burden approaches. RESULTS: We identified four novel loss-of-function variants in three genes, MTHFR, DLC1, and ITGB1, previously associated with NTD. Notably, DLC1 carried two protein truncating variants in two independent cases. We also demonstrated an enrichment of variants in MYO1E involved in cytoskeletal remodeling. This enrichment reached borderline significance in a replication cohort supporting the association of this new candidate gene to NTD. CONCLUSION: These data provide some key insights into the pathogenic mechanisms of human NTD and demonstrate the power of next-generation sequencing in deciphering the genetics of this complex trait.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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".