The Genetic Architecture of Congenital Diarrhea and Enteropathy
Bibliographic record
Abstract
Background Next-generation sequencing has enabled precision therapeutic approaches that have improved the lives of children with rare diseases. Congenital diarrhea and enteropathies (CODEs) are associated with high morbidity and mortality. Although treatment of these disorders is largely supportive, emerging targeted therapies based on genetic diagnoses include specific diets, pharmacologic treatments, and surgical interventions. Methods We analyzed the exomes or genomes of infants with suspected monogenic congenital diarrheal disorders. Using cell and zebrafish models, we tested the effects of variants in newly implicated genes. Results In our case series of 129 infant probands with suspected monogenic congenital diarrheal disorders, we identified causal variants, including a new founder NEUROG3 variant, in 62 infants (48%). Using cell and zebrafish models, we also uncovered and functionally characterized three novel genes associated with CODEs: GRWD1 , MYO1A , and MON1A . Conclusions We have characterized the broad genetic architecture of CODE disorders in a large case series of patients and identified three novel genes associated with CODEs. (Funded by the National Institutes of Health and others.)
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".