Absence of mutations in NR2E1 and SNX3in five patients with MMEP (microcephaly, microphthalmia, ectrodactyly, and prognathism) and related phenotypes
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Bibliographic record
Abstract
BACKGROUND: A disruption of sorting nexin 3 (SNX3) on 6q21 was previously reported in a patient with MMEP (microcephaly, microphthalmia, ectrodactyly, and prognathism) and t(6;13)(q21;q12) but no SNX3 mutations were identified in another sporadic case of MMEP, suggesting involvement of another gene. In this work, SNX3 was sequenced in three patients not previously studied for this gene. In addition, we test the hypothesis that mutations in the neighbouring gene NR2E1 may underlie MMEP and related phenotypes. METHODS: Mutation screening was performed in five patients: the t(6;13)(q21;q12) MMEP patient, three additional patients with possible MMEP or a related phenotype, and one patient with oligodactyly, ulnar aplasia, and a t(6;7)(q21;q31.2) translocation. We used sequencing to exclude SNX3 coding mutations in three patients not previously studied for this gene. To test the hypothesis that mutations in NR2E1 may contribute to MMEP or related phenotypes, we sequenced the entire coding region, complete 5' and 3' untranslated regions, consensus splice-sites, and evolutionarily conserved regions including core and proximal promoter in all five patients. Two-hundred and fifty control subjects were genotyped for any candidate mutation. RESULTS: We did not detect any synonymous nor nonsynonymous coding mutations of NR2E1 or SNX3. In one patient with possible MMEP, we identified a candidate regulatory mutation that has been reported previously in a patient with microcephaly but was not found in 250 control subjects examined here. CONCLUSION: Our results do not support involvement of coding mutations in NR2E1 or SNX3 in MMEP or related phenotypes; however, we cannot exclude the possibility that regulatory NR2E1 or SNX3 mutations or deletions at this locus may underlie abnormal human cortical development in some patients.
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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 it