Genetic diagnosis in Lafora disease
Bibliographic record
Abstract
Lafora disease (LD) can be diagnosed by skin biopsy, but this approach has both false negatives and false positives. Biopsies of other organs can also be diagnostic but are more invasive. Genetic diagnosis is also possible but can be inconclusive, for example, in patients with only one heterozygous EPM2A mutation and patients with apparently homozygous EPM2B mutations where one parent is not a carrier of the mutation. We sought to identify occult mutations and clarify the genotypes and confirm the diagnosis of LD in patients with apparent nonrecessive disease inheritance. We used single nucleotide polymorphism, quantitative PCR, and fluorescent in situ hybridization analyses. We identified large EPM2A and EPM2B deletions undetectable by PCR in the heterozygous state and describe simple methods for their routine detection. We report a coding sequence change in several patients and describe why the pathogenic role of this change remains unclear. We confirm that adult-onset LD is due to EPM2B mutations. Finally, we report major intrafamilial heterogeneity in age at onset in LD.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".