Mild cognitive impairment in novel SPG11 mutation-related sporadic hereditary spastic paraplegia with thin corpus callosum: case series
Bibliographic record
Abstract
BACKGROUND: SPG11 mutation-related autosomal recessive hereditary spastic paraplegia with thin corpus callosum (HSP-TCC) is the most common cause in complicated forms of HSP, usually presenting comprehensive mental retardation on early-onset stage preceding spastic paraplegias in childhood. However, there are many instances of sporadic late-onset HSP-TCC cases with a negative family history, and potential mild cognitive deficits in multiple domains may be easily neglected and inaccurately described. METHODS: In this study, we performed next generation sequencing in four sporadic late-onset patients with HSP-TCC, and combined Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) to evaluate cognition of the patients. RESULTS: By evolutionary conservation and structural modeling analysis, we have revealed 4 novel pathogenic SPG11 mutations, and firstly confirmed mild cognitive impairment (MCI) with normal MMSE scores (≥27) and decreased MoCA scores (< 26) in these SPG11 mutation-related HSP-TCC patients, predominantly presenting impairment of executive function, delayed recall, abstraction and language. CONCLUSIONS: The results expand the mutational spectrum of SPG11-associated HSP-TCC from sporadic cases, and confirm MCI with combination of decreased MoCA and normal MMSE assessment, suggesting that clinicians should consider doing a MoCA to detect MCI in patients with HSP, particularly those with HSP-TCC.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".