Huntington's disease–like 2 (HDL2) in North America and Japan
Bibliographic record
Abstract
Huntington's Disease-like 2 (HDL2) is a progressive, autosomal dominant, neurodegenerative disorder with marked clinical and pathological similarities to Huntington's disease (HD). The causal mutation is a CTG/CAG expansion mutation on chromosome 16q24.3, in a variably spliced exon of junctophilin-3. The frequency of HDL2 was determined in nine independent series of patients referred for HD testing or selected for the presence of an HD-like phenotype in North America or Japan. The repeat length, ancestry, and age of onset of all North American HDL2 cases were determined. The results show that HDL2 is very rare, with a frequency of 0 to 15% among patients in the nine case series with an HD-like presentation who do not have the HD mutation. HDL2 is predominantly, and perhaps exclusively, found in individuals of African ancestry. Repeat expansions ranged from 44 to 57 triplets, with length instability in maternal transmission detected in a repeat of r2=0.29, p=0.0098). The results further support the evidence that the repeat expansion at the chromosome 16q24.3 locus is the direct cause of HDL2 and provide preliminary guidelines for the genetic testing of patients with an HD-like phenotype.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".