Quantitative phenotypic and network analysis of 1q44 microdeletion for microcephaly
Bibliographic record
Abstract
As genome wide techniques become more common, an increasing proportion of patients with intellectual disability (ID) are found to have genetic defects allowing genotype-phenotype correlations. Previously, AKT3 deletion was suggested to be responsible for microcephaly in patients with 1q43-q44 deletion syndrome, but this does not correspond to all cases. We report a case of a de novo 1q44 deletion in an 8-year-old boy with microcephaly in whom AKT3 is not deleted. We used a systematic review of the literature, our patient, and network analysis to gain a better understanding of the genetic basis of microcephaly in 1q deletion patients. Our analysis showed that while AKT3 deletion is associated with more severe (≤3 SD) microcephaly in 1q43-q44 deletion patients, other genes may contribute to microcephaly in AKT3 intact patients with microcephaly and 1q43-44 deletion syndrome. We identified a potential role for HNRNPU, SMYD3, NLRP3, and KIF26B in microcephaly. Overall, our study highlights the need for network analysis and quantitative measures reporting in the phenotypic analysis of a complex genetic syndrome related to copy number variation.
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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) | 0.000 | 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".