Detection and Characterization of a De Novo <i>Alu</i> Retrotransposition Event Causing <i><scp>NKX2</scp>‐1</i>‐Related Disorder
Bibliographic record
Abstract
BACKGROUND: Heterozygous NKX2-1 loss-of-function variants cause combinations of hyperkinetic movement disorders (MDs, particularly childhood-onset chorea), pulmonary dysfunction, and hypothyroidism. Mobile element insertions (MEIs) are potential disease-causing structural variants whose detection in routine diagnostics remains challenging. OBJECTIVE: To establish the molecular diagnosis of two first-degree relatives with clinically suspected NKX2-1-related disorder who had negative NKX2-1 Sanger (SS), whole-exome (WES), and whole-genome (WGS) sequencing. METHODS: The proband's WES was analyzed for MEIs. A candidate MEI in NKX2-1 underwent optimized SS after plasmid cloning. Functional studies exploring NKX2-1 haploinsufficiency at RNA and protein levels were performed. RESULTS: A 347-bp AluYa5 insertion with a 65-bp poly-A tail followed by a 16-bp duplication of the pre-insertion wild-type sequence in exon 3 of NKX2-1 (ENST00000354822.7:c.556_557insAlu541_556dup) segregated with the disease phenotype. CONCLUSIONS: We identified a de novo exonic AluYa5 insertion causing NKX2-1-related disorder in SS/WES/WGS-negative cases, suggesting that MEI analysis of short-read sequencing data or targeted long-read sequencing could unmask the molecular diagnosis of unsolved MD cases. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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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".