Highly variable hearing loss due to POU4F3 (c.37del) is revealed by longitudinal, frequency specific analyses
Bibliographic record
Abstract
Genotype-phenotype correlations add value to the management of families with hereditary hearing loss (HL), where age-related typical audiograms (ARTAs) are generated from cross-sectional regression equations and used to predict the audiogram phenotype across the lifespan. A seven-generation kindred with autosomal dominant sensorineural HL (ADSNHL) was recruited and a novel pathogenic variant in POU4F3 (c.37del) was identified by combining linkage analysis with whole exome sequencing (WES). POU4F3 is noted for large intrafamilial variation including the age of onset of HL, audiogram configuration and presence of vestibular impairment. Sequential audiograms and longitudinal analyses reveal highly variable audiogram features among POU4F3 (c.37del) carriers, limiting the utility of ARTAs for clinical prognosis and management of HL. Furthermore, a comparison of ARTAs against three previously published families (1 Israeli Jewish, 2 Dutch) reveals significant interfamilial differences, with earlier onset and slower deterioration. This is the first published report of a North American family with ADSNHL due to POU4F3, the first report of the pathogenic c.37del variant, and the first study to conduct longitudinal analysis, extending the phenotypic spectrum of DFNA15.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".