Spectrum of SPG4 Mutations in a Large Collection of North American Families With Hereditary Spastic Paraplegia
Bibliographic record
Abstract
BACKGROUND: Hereditary spastic paraplegia (HSP) is a neurodegenerative disease characterized by progressive spasticity and weakness of the lower limbs. The most common form of HSP is caused by mutations in the SPG4 gene, which codes for spastin, an adenosine triphosphatase with various cellular activities (AAA) protein family member. OBJECTIVE: To investigate a large collection of predominantly North American patients with HSP for mutations in the spastin encoding gene, SPG4. METHODS: DNA from 76 unrelated affected individuals was studied for mutations by single-stranded conformational polymorphism analysis and direct sequencing. Each new variant identified was then analyzed in 80 control subjects to determine whether the variant is a common polymorphism or a rare mutation. All DNA samples were amplified by polymerase chain reaction, followed by electrophoresis and autoradiography. RESULTS: We identified 8 novel mutations and 5 previously reported mutations in 15 affected individuals. The novel mutations are 4 missense, 1 nonsense, 1 frameshift, and 2 splice mutations. Two polymorphisms (one in an affected individual) were also identified. CONCLUSIONS: Our collection of families with HSP is different on a genetic level from those previously described. The percentage of our families with a SPG4 mutation is 10% lower than the 40% estimate of families with autosomal dominant HSP noted to be linked to this locus, and splice mutations are not predominant in our collection. Interestingly, we also identified 2 recurring mutations in specific populations (R562Q and G559D), which may facilitate the development of future spastin diagnostic testing in these populations.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".