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Record W3018147106 · doi:10.1002/ana.25751

Clinico‐Genetic, Imaging and Molecular Delineation of <scp><i>COQ8A</i></scp>‐Ataxia: A Multicenter Study of 59 Patients

2020· article· en· W3018147106 on OpenAlexaff
Andreas Traschütz, Tommaso Schirinzi, Lucia Laugwitz, Nathan H. Murray, C.A. Bingman, Selina Reich, Jan Marco Kern, Anna Heinzmann, Gessica Vasco, Enrico Bertini, Ginevra Zanni, Alexandra Dürr, Stefania Magri, Franco Taroni, Alessandro Malandrini, Jonathan Baets, Peter De Jonghe, Willem De Ridder, Matthieu Béreau, Stephanie Demuth, Christos Ganos, A. Nazlı Başak, Haşmet Hanağası, Semra Hız Kurul, Benjamin Bender, Lüdger Schöls, Ute Grasshoff, Thomas Klopstock, Rita Horváth, Bart van de Warrenburg, Lydie Bürglen, Christelle Rougeot, Claire Ewenczyk, Michel Kœnig, Filippo M. Santorelli, Mathieu Anheim, Renato P. Munhoz, Tobias B. Haack, Felix Distelmaier, David J. Pagliarini, Hélène Puccio, Matthis Synofzik

Bibliographic record

VenueAnnals of Neurology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCoenzyme Q10 studies and effects
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersH2020 European Research CouncilHersenstichtingMedical Research CouncilVolkswagen FoundationNational Institutes of HealthUniversiteit AntwerpenMinistero della SaluteKoç ÜniversitesiNational Institute of General Medical SciencesBundesministerium für Bildung und ForschungEberhard Karls Universität TübingenActelion PharmaceuticalsErciyes ÜniversitesiDeutsche ForschungsgemeinschaftEuropean CommissionWellcome TrustAgence Nationale de la RechercheVlaamse regeringE-RareZonMwNewton FundFonds Wetenschappelijk OnderzoekRadboud UniversiteitUniversity of KentuckyNational Science Foundation
KeywordsAtaxiaMissense mutationAtrophyCohortMedicineMagnetic resonance imagingHyperintensityNeuroimagingDystoniaPediatricsInternal medicinePsychologyPathologyPsychiatryGeneticsPhenotypeBiologyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To foster trial-readiness of coenzyme Q8A (COQ8A)-ataxia, we map the clinicogenetic, molecular, and neuroimaging spectrum of COQ8A-ataxia in a large worldwide cohort, and provide first progression data, including treatment response to coenzyme Q10 (CoQ10). METHODS: Cross-modal analysis of a multicenter cohort of 59 COQ8A patients, including genotype-phenotype correlations, 3D-protein modeling, in vitro mutation analyses, magnetic resonance imaging (MRI) markers, disease progression, and CoQ10 response data. RESULTS: Fifty-nine patients (39 novel) with 44 pathogenic COQ8A variants (18 novel) were identified. Missense variants demonstrated a pleiotropic range of detrimental effects upon protein modeling and in vitro analysis of purified variants. COQ8A-ataxia presented as variable multisystemic, early-onset cerebellar ataxia, with complicating features ranging from epilepsy (32%) and cognitive impairment (49%) to exercise intolerance (25%) and hyperkinetic movement disorders (41%), including dystonia and myoclonus as presenting symptoms. Multisystemic involvement was more prevalent in missense than biallelic loss-of-function variants (82-93% vs 53%; p = 0.029). Cerebellar atrophy was universal on MRI (100%), with cerebral atrophy or dentate and pontine T2 hyperintensities observed in 28%. Cross-sectional (n = 34) and longitudinal (n = 7) assessments consistently indicated mild-to-moderate progression of ataxia (SARA: 0.45/year). CoQ10 treatment led to improvement by clinical report in 14 of 30 patients, and by quantitative longitudinal assessments in 8 of 11 patients (SARA: -0.81/year). Explorative sample size calculations indicate that ≥48 patients per arm may suffice to demonstrate efficacy for interventions that reduce progression by 50%. INTERPRETATION: This study provides a deeper understanding of the disease, and paves the way toward large-scale natural history studies and treatment trials in COQ8A-ataxia. ANN NEUROL 2020;88:251-263.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.288
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations77
Published2020
Admission routes1
Has abstractyes

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