Anticipation Can Be More Common in Hereditary Spastic Paraplegia with <i>SPAST</i> Mutations Than It Appears
Bibliographic record
Abstract
ABSTRACT: Background and objective: Hereditary spastic paraplegia (HSP) is a heterogeneous neurodegenerative disorder with lower-limb spasticity and weakness. Different patterns of inheritance have been identified in HSP. Most autosomal-dominant HSPs (AD-HSPs) are associated with mutations of the SPAST gene (SPG4), leading to a pure form of HSP with variable age-at-onset (AAO). Anticipation, an earlier onset of disease, as well as aggravation of symptoms in successive generations, may be correlated to SPG4. Herein, we suggested that anticipation might be a relatively common finding in SPG4 families. Methods: Whole-exome sequencing was done on DNA of 14 unrelated Iranian AD-HSP probands. Data were analyzed, and candidate variants were PCR-amplified and sequenced by the Sanger method, subsequently checked in family members to co-segregation analysis. Multiplex ligation-dependent probe amplification (MLPA) was done for seven probands. Clinical features of the probands were recorded, and the probable anticipation was checked in these families. Other previous reported SPG4 families were investigated to anticipation. Results: Our findings showed that SPG4 was the common subtype of HSP; three families carried variants in the KIF5A, ATL1, and MFN2 genes, while five families harbored mutations in the SPAST gene. Clinical features of only SPG4 families indicated decreasing AAO in affected individuals of the successive generations, and this difference was significant (p-value <0.05). Conclusion: It seems SPAST will be the first candidate gene in families that manifests a pure form of AD-HSP and anticipation. Therefore, it may be a powerful situation of genotype–phenotype correlation. However, the underlying mechanism of anticipation in these families is not clear yet.
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 | 0.001 | 0.001 |
| 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) | 0.004 | 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".