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Record W4407348700 · doi:10.1002/mds.30143

The Pattern and Stages of Atrophy in Spinocerebellar Ataxia Type 2: Volumetrics from <scp>ENIGMA</scp>‐Ataxia

2025· article· en· W4407348700 on OpenAlexafffund
Jason W. Robertson, Isaac Adanyeguh, Benjamin Bender, Sylvia Boesch, Arturo Brunetti, Sirio Cocozza, Léo Coutinho, Andreas Deistung, Stefano Diciotti, Imis Dogan, Alexandra Dürr, Juan Fernández-Ruíz, Sophia Göricke, Marina Grisoli, Shuo Han, Caterina Mariotti, Chiara Marzi, Mario Mascalchi, Fanny Mochel, Wolfgang Nachbauer, Lorenzo Nanetti, Anna Nigri, Sergio Eiji Ono, Chiadi U. Onyike, Jerry L. Prince, Kathrin Reetz, Sandro Romanzetti, Francesco Saccà, Matthis Synofzik, Hélio Afonso Ghizoni Teive, Sophia I. Thomopoulos, Paul M. Thompson, Dagmar Timmann, Sarah H. Ying, Ian H. Harding, Carlos R. Hernandez‐Castillo

Bibliographic record

VenueMovement Disorders · 2025
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsDalhousie University
FundersNational Health and Medical Research CouncilMedical Research CouncilMinistero della SaluteNational Institute of Neurological Disorders and StrokeBundesministerium für Bildung und ForschungNational Institutes of HealthCanada Research ChairsNational Ataxia FoundationDeutsche ForschungsgemeinschaftDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoNatural Sciences and Engineering Research Council of CanadaJohns Hopkins UniversityNational Center for Advancing Translational SciencesConsejo Nacional de Ciencia y TecnologíaNational Science Foundation
KeywordsSpinocerebellar ataxiaCerebellumNeuroscienceAtrophyWhite matterBrainstemAtaxiaVoxel-based morphometryPsychologyPonsNeurodegenerationCerebellar cortexCerebellar ataxiaThalamusPathologyMagnetic resonance imagingAnatomyMedicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Spinocerebellar ataxia type 2 (SCA2) is a rare, inherited neurodegenerative disease characterized by progressive deterioration in both motor coordination and cognitive function. Atrophy of the cerebellum, brainstem, and spinal cord are core features of SCA2; however, the evolution and pattern of whole-brain atrophy in SCA2 remain unclear. OBJECTIVE: We undertook a multisite, structural magnetic resonance imaging (MRI) study to comprehensively characterize the neurodegeneration profile of SCA2. METHODS: Voxel-based morphometry analyses of 110 participants with SCA2 and 128 controls were undertaken to assess groupwise differences in whole-brain volume. Correlations with clinical severity and genotype, and cross-sectional profiling of atrophy patterns at different disease stages, were also performed. RESULTS: Atrophy in SCA2 versus controls was greatest (Cohen's d >2.5) in the cerebellar white matter (WM), middle cerebellar peduncle, pons, and corticospinal tract. Very large effects (d >1.5) were also evident in the superior cerebellar, inferior cerebellar, and cerebral peduncles. In the cerebellar gray matter (GM), large effects (d >0.8) were observed in areas related to both motor coordination and cognitive tasks. Strong correlations (|r| > 0.4) between volume and disease severity largely mirrored these groupwise outcomes. Stratification by disease severity exhibited a degeneration pattern beginning in the cerebellar and pontine WM in preclinical subjects; spreading to the cerebellar GM and cerebro-cerebellar/corticospinal WM tracts; and then finally involving the thalamus, striatum, and cortex in severe stages. CONCLUSION: The magnitude and pattern of brain atrophy evolve over the course of SCA2, with widespread, nonuniform involvement across the brainstem, cerebellar tracts, and cerebellar cortex; and late involvement of the cerebral cortex and striatum. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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".

Quick stats

Citations4
Published2025
Admission routes2
Has abstractyes

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