Autosomal Recessive Cerebellar Ataxias in Europe: Frequency, Onset, and Severity in 677 Patients
Bibliographic record
Abstract
Autosomal Recessive Cerebellar Ataxias in Europe: Frequency, Onset, and Severity in 677 PatientsProgress in next-generation sequencing has led to an explosion of novel genes and phenotypes of autosomal recessive cerebellar ataxias (ARCAs) in the last decade, with >170 recessive conditions manifesting with ataxia identified. 1 With large-scale natural history and mechanistic treatment trials on the horizon for many ARCAs, up-to-date knowledge is required not only on relative frequencies but also on real-world age and disease severity distributions as key information for trial design planning and recruitment.In this multicenter study, we provide data on the relative frequency of ARCAs in Europe, delineate the spectrum of age at disease onset, and present realworld data on disease severity distributions of patients with ARCA that help to inform future trial planning.Prospective cross-sectional and longitudinal data from consecutive patients enrolled between 2013 and June 2022 from 23 European sites (Fig. 1A) were included, all collected through the international ARCA Registry.2 Patients had been eligible for inclusion into the ARCA Registry if they had (1) a genetically confirmed ARCA; and/or (2) onset before age 40 years without evidence of an autosomal dominant family history, repeat expansion in spinocerebellar ataxia genes, or acquired cause, thus representing a stratum of patients with ataxia known to be enriched for recessive ataxia disease.3,4 Patients with Friedreich's ataxia (FA; n = 112) were not included because (1) FA is already covered in parallel by other European natural history registries (eg, EFACTS), 5 which would lead to a distorted, nonrepresentative frequency estimate in the current study; (2) this study focused on the rare and less well-studied ARCAs; and (3) disease data as investigated in this study are thus already available elsewhere.5 A total of 677 patients were included in this study, rendering it the largest European ARCA frequency study to date.Fiftynine percent had a genetic diagnosis (Fig. 1B), with autosomal recessive spastic ataxia Charlevoix-Saguenay (ARSACS; 13%) and spastic paraplegia type 7 (SPG7; 10%) being the most frequent, followed by RFC1, ataxia with oculomotor apraxia type 2 (AOA2), ataxia telangiectasia (AT), and SYNE1 (all 7%), and then in decreasing frequency, COQ8A (5%), POLG (4%), ANO10 (3%), and AOA1 (3%), and a large number of 62 ultra-rare ARCAs (each ≤2%, often only n = 1-3 patients/ ARCA) (Fig. 1C).Age of onset of ARSACS, AT, and COQ8A was typically in the first decade of life (Fig. 1D), whereas SPG7, POLG, and ANO10 started on average in the fourth decade.Patients with RFC1 mutations had a later onset, on average at age 53 (interquartile range: 49-61) years (Fig. 1D).Cross-sectional disease progression estimates (Scale for the Assessment and Rating of Ataxia score [SARA]/disease duration) suggest a relatively faster disease progression for AT (median: 1.4 SARA points/years), but a slower disease progression for ARSACS (0.6 SARA point/years), RFC1 (0.9 SARA point/years), and SPG7 (0.6 SARA point/years) (Fig. 1F,G).Most patients with ARCA currently attending ataxia clinics ---------------------------------------
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".