Brain atrophy staging in spinocerebellar ataxia type 3 for clinical prognosis and trial enrichment
(2026) In EBioMedicine 123.- Abstract
- Background: 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. Methods: 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... (More)
- Background: 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. Methods: 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. Findings: 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. Interpretation: 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. Funding: National Ataxia Foundation (NAF). © 2025 The Author(s) (Less)
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https://lup.lub.lu.se/record/a960039b-7a64-42b4-b109-8ff855d06932
- author
- Baumeister, H. ; Berron, D. LU and Faber, Jennifer
- author collaboration
- organization
- publishing date
- 2026
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Ataxia, Disease progression modelling, Imaging biomarker, Machine learning, Movement disorders, Adult, Aged, Atrophy, Brain, Disease Progression, Female, Humans, Machado-Joseph Disease, Magnetic Resonance Imaging, Male, Middle Aged, Prognosis, Severity of Illness Index, ataxin 3, adherence intervention, adult, Article, ataxia, brain atrophy, brain size, clinical outcome, controlled study, cost benefit analysis, disease classification, disease severity, female, follow up, gait, gene frequency, gene mutation, human, INAS count, intervention study, intracranial volume, major clinical study, male, neuroimaging, nuclear magnetic resonance imaging, observational study, patient stratification, phenotype, post hoc analysis, prevalence, prognosis, proportional hazards model, prospective study, quality control, rehabilitation care, risk factor, root mean squared error, Scale for the Assessment and Rating of Ataxia, sensitivity analysis, T1 weighted imaging, threshold limit value, training, validation process, white matter, aged, atrophy, brain, diagnosis, diagnostic imaging, disease exacerbation, genetics, Machado Joseph disease, middle aged, pathology, severity of illness index
- in
- EBioMedicine
- volume
- 123
- article number
- 106090
- publisher
- Elsevier
- external identifiers
-
- scopus:105025476950
- pmid:41443080
- ISSN
- 2352-3964
- DOI
- 10.1016/j.ebiom.2025.106090
- language
- English
- LU publication?
- yes
- id
- a960039b-7a64-42b4-b109-8ff855d06932
- date added to LUP
- 2026-03-24 12:32:42
- date last changed
- 2026-03-25 03:00:01
@article{a960039b-7a64-42b4-b109-8ff855d06932,
abstract = {{Background: 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. Methods: 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. Findings: 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. Interpretation: 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. Funding: National Ataxia Foundation (NAF). © 2025 The Author(s)}},
author = {{Baumeister, H. and Berron, D. and Faber, Jennifer}},
issn = {{2352-3964}},
keywords = {{Ataxia; Disease progression modelling; Imaging biomarker; Machine learning; Movement disorders; Adult; Aged; Atrophy; Brain; Disease Progression; Female; Humans; Machado-Joseph Disease; Magnetic Resonance Imaging; Male; Middle Aged; Prognosis; Severity of Illness Index; ataxin 3; adherence intervention; adult; Article; ataxia; brain atrophy; brain size; clinical outcome; controlled study; cost benefit analysis; disease classification; disease severity; female; follow up; gait; gene frequency; gene mutation; human; INAS count; intervention study; intracranial volume; major clinical study; male; neuroimaging; nuclear magnetic resonance imaging; observational study; patient stratification; phenotype; post hoc analysis; prevalence; prognosis; proportional hazards model; prospective study; quality control; rehabilitation care; risk factor; root mean squared error; Scale for the Assessment and Rating of Ataxia; sensitivity analysis; T1 weighted imaging; threshold limit value; training; validation process; white matter; aged; atrophy; brain; diagnosis; diagnostic imaging; disease exacerbation; genetics; Machado Joseph disease; middle aged; pathology; severity of illness index}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{EBioMedicine}},
title = {{Brain atrophy staging in spinocerebellar ataxia type 3 for clinical prognosis and trial enrichment}},
url = {{http://dx.doi.org/10.1016/j.ebiom.2025.106090}},
doi = {{10.1016/j.ebiom.2025.106090}},
volume = {{123}},
year = {{2026}},
}