Bibliographic record
Abstract
Early-onset movement disorders such as dystonia, chorea ataxia, Parkinsonism or spasticity and can be disabling, stigmatising, painful and in extreme cases life-threatening.Although cerebral palsy due to perinatal brain injuries is the commonest cause, genetic disorders are increasingly recognised as a major contributor.A high proportion of these conditions remain undiagnosed -and undiagnosable -as the causative gene has not yet been found.Furthermore, interpreting the results of genetic tests is impeded by our incomplete understanding of the full range of possible presentations, especially in ultra-rare genetic disorders.166 families with suspected genetic movement disorders were investigated using whole-genome sequencing (WGS).By combining detailed clinical phenotyping with either very broad gene panels or panel-free/gene-agnostic analysis, we aimed to identify variants in genes not previously associated with a disease phenotype, or for which the phenotype was inadequately reported.Where a likely new disease-gene relationship was identified, we investigated further through laboratory investigation including studies of splicing, gene expression and protein localisation and by case-finding in collaboration with other research groups.This project identified three novel genetic causes of movement disorders (VPS16, the cause of dystonia 30, VPS41, cause of autosomal recessive spinocerebellar ataxia 29 and DRD1, implicated in infantile dystonia-parkinsonism), and contributed to the identifying three more.Many other participants had presentations which expanded the known phenotypic spectrum of their disorder, including those with variants in SLC30A9, RHOBTB2, and JPH3.The analysis detected findings suspected to be relevant in 45.2% (75/166) of participants, including a probable diagnosis in 32.5% (54/166), despite a high level of pre-recruitment investigation in many.Overall, one participant with an identifiable previously undescribed genetic disorder was identified for every 19 analyses conducted.This high rate of significant findings confirms the value of WGS in populations with rare childhood movement disorders as a tool both for diagnosis and for gene discovery.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.811 | 0.603 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".