TY  - JOUR
AU  - Baumeister, Hannah
AU  - Wegner, Philipp
AU  - Ferreira, Mónica
AU  - Schaprian, Tamara
AU  - França, Marcondes C
AU  - Rezende, Thiago Junqueira Ribeiro
AU  - Muro Martinez, Alberto Rolim
AU  - Jiang, Hong
AU  - Chen, Zhao
AU  - Weihua, Liao
AU  - Grobe-Einsler, Marcus
AU  - Koyak, Berkan
AU  - Önder, Demet
AU  - van de Warrenburg, Bart
AU  - van Gaalen, Judith
AU  - Durr, Alexandra
AU  - Coarelli, Giulia
AU  - Synofzik, Matthis
AU  - Schöls, Ludger
AU  - Giunti, Paola
AU  - Garcia-Moreno, Hector
AU  - Öz, Gülin
AU  - Joers, James
AU  - Timmann, Dagmar
AU  - Thieme, Andreas G
AU  - Jacobi, Heike
AU  - de Vries, Jeroen
AU  - Barker, Peter
AU  - Onyike, Chiadikaobi
AU  - Ratai, Eva-Maria
AU  - Schmahmann, Jeremy D
AU  - Reetz, Kathrin
AU  - Infante, Jon
AU  - Huebener-Schmid, Jeannette
AU  - Kuegler, David
AU  - Klockgether, Thomas
AU  - Berron, David
AU  - Faber, Jennifer
TI  - Brain atrophy staging in spinocerebellar ataxia type 3 for clinical prognosis and trial enrichment.
JO  - EBioMedicine
VL  - 123
SN  - 2352-3964
CY  - Amsterdam [u.a.]
PB  - Elsevier
M1  - DZNE-2026-00072
SP  - 106090
PY  - 2026
AB  - Spinocerebellar ataxia type 3 (SCA3) is characterised by progressive brain atrophy, with regional volume loss detectable via MRI prior to clinical manifestation. We aimed to identify the previously unknown sequence of brain atrophy in SCA3 and evaluate whether this sequence can be translated into an atrophy staging framework to enable accurate clinical prognosis and trial enrichment.We included data from 322 SCA3 mutation carriers, enrolled in observational studies conducted across Europe, the Americas, and Asia. Participants underwent follow-up assessments up to five years after baseline. The Subtype and Stage Inference machine learning algorithm was applied to estimate the most likely atrophy sequence(s) from baseline anatomical MRI. The Scale for the Assessment and Rating of Ataxia (SARA) was used to capture ataxia severity. Atrophy stages were analysed in relation to SARA and time from disease onset. Interventional trials were simulated to estimate required sample sizes under different atrophy stage eligibility criteria.We identified a uniform sequence of brain atrophy in SCA3, characterised by earliest volumetric decline in the caudal brainstem and substantial involvement of the white matter. Atrophy stage was associated with both SARA and time from disease onset. Atrophy staging outperformed single-region volumetrics in predicting SARA over time. Applying atrophy stage cut-offs substantially reduced the sample sizes needed to adequately power hypothetical clinical trials.These findings yield mechanistic insights into the progression of neurodegeneration in SCA3 and possess immediate translational relevance, facilitating patient stratification and sample enrichment for interventional trials.National Ataxia Foundation (NAF).
KW  - Humans
KW  - Atrophy
KW  - Machado-Joseph Disease: pathology
KW  - Machado-Joseph Disease: diagnosis
KW  - Machado-Joseph Disease: genetics
KW  - Machado-Joseph Disease: diagnostic imaging
KW  - Prognosis
KW  - Male
KW  - Magnetic Resonance Imaging
KW  - Brain: pathology
KW  - Brain: diagnostic imaging
KW  - Female
KW  - Middle Aged
KW  - Adult
KW  - Disease Progression
KW  - Severity of Illness Index
KW  - Aged
KW  - Ataxia (Other)
KW  - Disease progression modelling (Other)
KW  - Imaging biomarker (Other)
KW  - Machine learning (Other)
KW  - Movement disorders (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:41443080
C2  - pmc:PMC12800623
DO  - DOI:10.1016/j.ebiom.2025.106090
UR  - https://pub.dzne.de/record/284029
ER  -