A recurrent <i>EYA1</i> mutation causing alternative RNA splicing in branchio‐oto‐renal syndrome: Implications for molecular diagnostics and disease mechanism
Bibliographic record
Abstract
Branchio-oto-renal syndrome is a heterogeneous disorder inherited in an autosomal dominant pattern, characterized by branchial arch abnormalities, hearing loss and renal abnormalities, with mutations in EYA1 reported in 30-70% of patients. We have applied a molecular testing strategy of sequencing of the complete coding region/flanking intronic regions and multiple ligation probe amplification analysis of EYA1 to a pediatric branchio-oto-renal proband cohort. EYA1 mutations were identified in 82% (14/17) of the probands. We also describe a novel recurrent EYA1 mutation c.867 + 5G > A found in five unrelated affected patients. RNA analysis showed that c.867 + 5G > A affects EYA1 splicing, producing an aberrant mRNA transcript lacking exon 8 and resulting in premature termination in exon 9. The aberrant transcript was present at approximately 50% level of wild-type EYA1 mRNA in fibroblasts, and is predicted to encode an EYA1 protein retaining the amino terminal transcriptional coactivator region but lacking the conserved carboxy terminal Eya phosphatase domain. Patients with the c.867 + 5G > A mutation were found to have more severe renal abnormalities than probands with other mutations in this cohort. Analysis of the c.867 + 5G > A mutation suggests that certain transcripts of EYA1 escape nonsense-mediated decay and encode truncated EYA proteins that may be capable of dominant-negative interactions producing distinct phenotypic features within the branchio-oto-renal spectrum.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".