Genotype-phenotype correlations in hereditary multiple exostoses in British Columbia
Bibliographic record
Abstract
Hereditary Multiple Exostosis is an autosomal dominant condition in which multiple benign cartilage-capped tumours grow in relation to the growth plates of long and flat bones. HME has a wide spectrum of clinical presentations and results in considerable morbidity from lesions due to mass effect causing limb deformity, mal-alignment, and shortening. Mutations in EXT 1 and 2 genes result in multiple exostoses. The presumptive role of the EXT genes is either tumour suppression or growth plate regulation. The purpose of this study was to determine the relationship between the genotype and phenotype in HME. Ten families were identified with HME. Genotyping was completed by linkage analysis of all families and the EXT 1 or 2 gene was sequenced based on these results. Mutation identification and confirmation was performed. Phenotyping consisting of clinical and radiographic examinations generated 89 features for each subject. Thirty-two affected individuals from 10 families participated. Eight of 10 mutations were identified, confirmed and segregation verified. Six of the mutations were unique and 2 previously had been reported in the literature. Three mutations were in EXT 1 and 5 in EXT 2. Two were missense, 3 nonsense, 2 splice site and 1 frameshift. EXT 1 patients were found to have more exostoses, with a higher percentage of flat and pelvic bone involvement. EXT 1 patients had more mal-alignment and were shorter. Males also had a more severe phenotype and modulated the severity of EXT 1 expression. No other genotypic factors were found to influence phenotype. An established genotype phenotype correlation will aid in patient management in terms of surveillance, determining prognosis and mangement. In conclusion a genotype phenotype correlation exists where EXT 1 is linked to a more severe phenotype.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".