Biallelic mutations in huntington disease: A new case with just one affected parent, review of the literature and terminology
Bibliographic record
Abstract
Patients with biallelic mutations for Huntington disease (HD) are rare. We present a 46-year-old female with two expanded Huntingtin (HTT) alleles with just one known affected parent. This is the first reported patient with molecular studies performed to exclude HTT uniparental disomy (UPD). The proband had biparental inheritance of HTT alleles (42/44 CAG repeats). Given the negative UPD results, the proband's unaffected mother either had a reduced penetrance allele that expanded into the full mutation range during transmission to our patient or an unknown full HTT mutation and died before symptom onset, unlikely given no family history of HD and asymptomatic at age 59. We made the novel observation in our literature review that most patients with biallelic HD did not have two full HTT mutations. Most had one HTT allele that was in the intermediate or reduced penetrance ranges or 40 CAG repeats, the lowest limit of the full mutation range. Although the number of patients is small, when an allele in these size ranges was present, generally the age of HD onset was in the 50s. If the second HTT allele had >45 repeats, then onset was typically 20s-30s. While similar ages of onset have been reported for patients with one or two HTT mutations, patients with biallelic mutations may have later onset if an expanded HTT allele has ≤40 CAG repeats. Finally, we propose that "biallelic mutations" or "compound heterozygosity" are more accurate descriptive terms than "homozygosity" when there are two non-identical expanded HTT alleles.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".