Autosomal Recessive Cerebellar Ataxias in Europe: Frequency, Onset, and Severity in 677 Patients
Notice bibliographique
Résumé
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 ---------------------------------------
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».