Onset and rate of striatal atrophy in preclinical Huntington disease
Bibliographic record
Abstract
BACKGROUND: Huntington disease (HD) is characterized by striatal atrophy that begins long before the onset of motor symptoms. OBJECTIVE: To determine when striatal atrophy begins, the extent and rate of atrophy before diagnosis of motor symptoms, and whether striatal atrophy can predict when symptom onset will occur. METHODS: Caudate and putamen volumes were measured on MRI scans of 19 preclinical subjects with the HD gene expansion who were very far (9 to 20 years) from estimated onset, and on serial scans from 17 preclinical subjects, six of whom were diagnosed with HD within 5 years after the initial scan. RESULTS: Striatal volumes were significantly smaller for the subjects who were very far from estimated onset than for age-matched control subjects. Statistical models fit to the longitudinal data suggest that rate of caudate atrophy becomes significant when subjects are approximately 11 years from estimated onset and rate of putamen atrophy becomes significant approximately 9 years prior to onset. In the six incident cases, caudate and putamen were approximately one-third to one-half of normal volume at diagnosis, and caudate volume alone was able to predict with 100% accuracy those subjects who would be diagnosed within 2 years of imaging. CONCLUSIONS: Striatal atrophy begins many years prior to diagnosable HD, and assessment of atrophy on MRI may be very useful in both predicting HD onset and in tracking progression in future therapeutic trials in preclinical subjects.
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 | 0.001 | 0.003 |
| 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".