Advanced Phenotyping of Otosclerosis in an Ontario Population and Two Large Newfoundland Families
Bibliographic record
Abstract
Otosclerosis is a relatively common hearing loss disorder characterized by abnormal bone growth in the otic capsule leading to stapes fixation. In approximately half of cases, otosclerosis is inherited as an autosomal dominant trait. Typically, gene discovery efforts rely on surgical confirmation, audiometry and occasionally acoustic reflexes to identify affected cases of otosclerosis within families, requiring that the otosclerosis was at an advanced stage to be detected. This makes it difficult to identify individuals with early otosclerosis. The use of advanced phenotyping to identify cases of otosclerosis was tested in an Ontario otosclerotic population as well as in two large Newfoundland families, one with otosclerosis due to a newly discovered deletion in the FOXL1 gene. Family history questionnaires revealed that approximately two-thirds of Ontario probands had a significant family history of non-congenital hearing loss with almost half of those probands reporting another family member with otosclerosis. Furthermore, all Ontario probands were screened for the FOXL1 deletion identified in the NL family, with one testing positive, providing evidence that FOXL1 may underlie cases of otosclerosis in other populations.\nThe otosclerotic phenotype of prospective data obtained in a surgically-confirmed Ontario cohort was quite variable with 30% of subjects presenting with unilateral otosclerosis and 9% presenting with sensorineural hearing loss (SNHL) in their non-surgical ear. Results suggest that distortion product otoacoustic emissions and acoustic reflex thresholds are absent in all surgical ears, SNHL ears and ears with a conductive hearing loss. To further enhance the advanced phenotyping of otosclerosis, power absorbance (PA) was analyzed to determine its utility as a phenotyping tool. Results suggest that PA has a valid test-retest reliability, but that instrument and stimulus effects are present.\nAdvanced phenotyping was used to develop a predictive model for FOXL1-associated otosclerosis suggesting a progressive mixed hearing loss. Phenotyping in a second large, non-FOXL1 family identified members with suspected early disease progression. Early identification of otosclerosis, without having to wait for a surgical confirmation, will aid future gene discovery research. Furthermore, insights gained from advanced phenotyping in sub-clinical gene carriers can provide a deeper understanding of the natural history of otosclerosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".