Extended mutation spectrum of Usher syndrome in Finland
Bibliographic record
Abstract
PURPOSE: The Finnish distribution of clinical Usher syndrome (USH) types is 40% USH3, 34% USH1 and 12% USH2. All patients with USH3 carry the founder mutation in clarin 1 (CLRN1), whereas we recently reported three novel myosin VIIA (MYO7A) mutations in two unrelated patients with USH1. This study was carried out to further investigate the USH mutation spectrum in Finnish patients. METHODS: We analysed samples from nine unrelated USH patients/families without known mutations and two USH3 families with atypically severe phenotype. The Asper Ophthalmics USH mutation chip was used to screen for known mutations and to evaluate the chip in molecular diagnostics of Finnish patients. RESULTS: The chip revealed a heterozygous usherin (USH2A) mutation, p.N346H, in one patient. Sequencing of MYO7A and/or USH2A in three index patients revealed two novel heterozygous mutations, p.R873W in MYO7A and c.14343+2T>C in USH2A. We did not identify definite pathogenic second mutations in the patients, but identified several probably nonpathogenic variations that may modify the disease phenotype. Possible digenism could not be excluded in two families segregating genomic variations in both MYO7A and USH2A, and two families with CLRN1 and USH2A. CONCLUSION: We conclude that there is considerable genetic heterogeneity of USH1 and USH2 in Finland, making molecular diagnostics and genetic counselling of patients and families challenging.
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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 | 0.001 |
| 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 | 0.000 | 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 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".