The genetic landscape of sporadic adult-onset degenerative ataxia: a multi-modal genetic study of 377 consecutive patients from the longitudinal multi-centre SPORTAX cohort
Bibliographic record
Abstract
BACKGROUND: While most sporadic adult-onset neurodegenerative diseases have only a minor monogenic component, given several recently identified late adult-onset ataxia genes, the genetic burden may be substantial in sporadic adult-onset ataxias. We report systematic mapping of the genetic landscape of sporadic adult-onset ataxia in a well-characterised, multi-centre cohort, combining several multi-modal genetic screening techniques, plus longitudinal natural history data. METHODS: ) (n = 148). Combined GAA-FGF14 (SCA27B) and RFC1 repeat expansion screening with next-generation sequencing (NGS) was complemented by natural history and plasma neurofilament light chain analysis in key subgroups. FINDINGS: ). Five patients (1.3%) were found to have two relevant genetic variants simultaneously (dual diagnosis). INTERPRETATION: criteria, suggesting a reduced specificity of this clinical diagnosis and potential co-occurrence of MSA-C plus a second, independent genetic condition. These findings have important implications for the genetic work-up and counselling of patients with sporadic ataxia, even when presenting with MSA-like features. With targeted treatments for genetic ataxias now on the horizon, these findings highlight their potential utility for these patients. FUNDING: This work was supported by the Clinician Scientist programme "PRECISE.net" funded by the Else Kröner-Fresenius-Stiftung (to DM, AT, CW, OR, and MS), by the Deutsche Forschungsgemeinschaft (as part of the PROSPAX project), and by the Canadian Institutes of Health Research and the Fondation Groupe Monaco. Support was also provided by Humboldt Research Fellowship for Postdocs and the Hertie-Network of Excellence in Clinical Neuroscience and a Fellowship award from the Canadian Institutes of Health Research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".