Abstract
Abstract

Background
Spinocerebellar ataxia type 1 (SCA1) is a rare, autosomal dominant neurodegenerative disorder characterized by progressive cerebellar and brainstem degeneration. Previous studies have shown that spinal cord atrophy is also a key aspect of SCA1 neuropathology. Magnetic resonance imaging (MRI)‐based spinal cord measurements could, therefore, serve as staging or monitoring biomarkers. However, previous findings were limited to cross‐sectional analyses, and longitudinal changes remain unexplored.


Objectives
This study investigates both cross‐sectional and longitudinal cervical spinal cord alterations in SCA1 mutation carriers compared to healthy controls, evaluating the utility of this biomarker.


Methods
Baseline and 1‐year MRI changes were assessed in 40 controls, 16 preataxic and 58 symptomatic SCA1 mutation carriers. T1‐weighed images were processed with FreeSurfer and the Spinal Cord Toolbox. We related Z‐scores to disease duration, calculated standardized response means, and analyzed clinico‐genetic associations using a linear mixed model.


Results
The three groups differed significantly in cross‐sectional area (CSA) at all levels at baseline. Over time, CSA at levels C1 and C2 decreased in the preataxic and symptomatic groups compared to controls. Preataxic carriers already showed pronounced spinal cord atrophy, whereas pontine changes emerged later in the disease course. Standardized response means were highest for CSA at C2 in preataxic stage, whereas this was pontine volume at symptomatic stage, indicating region‐specific biomarkers across disease stages.


Conclusion

Cervical spinal cord atrophy is an early and progressive feature of SCA1, detectable before clinical onset, providing a promising imaging biomarker for early disease stages. Our findings suggest a caudal to rostral progression of atrophy in SCA1. © 2026 The Author(s).
Movement Disorders
published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. © 2026 The Author(s).
Movement Disorders
published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Topics

No keywords indexed for this article. Browse by subject →

References
48
[1]
Zoghbi HY "Spinocerebellar ataxia type 1" Semin Cell Biol (1995) 10.1016/1043-4682(95)90012-8
[2]
Diallo A "Natural history of most common spinocerebellar ataxia: a systematic review and meta‐analysis" J Neurol (2021) 10.1007/s00415-020-09815-2
[3]
Prooije TH "Multimodal, longitudinal profiling of SCA1 identifies predictors of disease severity and progression" Ann Neurol (2024) 10.1002/ana.27032
[4]
Fonteyn EMR "The effectiveness of allied health care in patients with ataxia: a systematic review" J Neurol (2014) 10.1007/s00415-013-6910-6
[5]
Sullivan R "Spinocerebellar ataxia: an update" J Neurol (2019) 10.1007/s00415-018-9076-4
[6]
Rezende TJR "Genotype‐specific spinal cord damage in spinocerebellar ataxias: an ENIGMA‐ataxia study" J Neurol Neurosurg Psychiatry (2024) 10.1136/jnnp-2023-332696
[7]
Martins CR "Spinal cord damage in spinocerebellar ataxia type 1" Cerebellum (2017) 10.1007/s12311-017-0854-9
[8]
Faber J "Regional brain and spinal cord volume loss in spinocerebellar ataxia type 3" Mov Disord (2021) 10.1002/mds.28610
[9]
Rüb U "Spinocerebellar ataxia type 1 (SCA1): new pathoanatomical and clinico‐pathological insights" Neuropathol Appl Neurobiol (2012) 10.1111/j.1365-2990.2012.01259.x
[10]
Iwabuchi K "Autosomal dominant spinocerebellar degenerations. Clinical, pathological, and genetic correlations" Rev Neurol (1999)
[11]
Huang L "Corticospinal tract: a new hope for the treatment of post‐stroke spasticity" Acta Neurol Belg (2024) 10.1007/s13760-023-02377-w
[12]
Abele M "Autosomal dominant cerebellar ataxia type I. Nerve conduction and evoked potential studies in families with SCA1, SCA2 and SCA3" Brain (1997) 10.1093/brain/120.12.2141
[13]
Warrenburg BPC "Peripheral nerve involvement in spinocerebellar ataxias" Arch Neurol (2004) 10.1001/archneur.61.2.257
[14]
Berger M "Progression of biological markers in spinocerebellar ataxia type 3: longitudinal analysis of prospective data from the ESMI cohort" Lancet Reg Health (2025)
[15]
Nigri A "Spinocerebellar ataxia type 1: one‐year longitudinal study to identify clinical and MRI measures of disease progression in patients and Presymptomatic carriers" Cerebellum (2022) 10.1007/s12311-021-01285-0
[16]
Coarelli G "Plasma neurofilament light chain predicts cerebellar atrophy and clinical progression in spinocerebellar ataxia" Neurobiol Dis (2021) 10.1016/j.nbd.2021.105311
[17]
Scale for the assessment and rating of ataxia

T. Schmitz-Hübsch, S. Tezenas du Montcel, L. Baliko et al.

Neurology 2006 10.1212/01.wnl.0000219042.60538.92
[18]
Tezenas Du Montcel S "Prediction of the age at onset in spinocerebellar ataxia type 1, 2, 3 and 6" J Med Genet (2014) 10.1136/jmedgenet-2013-102200
[19]
Subramony SH "SARA‐‐a new clinical scale for the assessment and rating of ataxia" Nat Clin Pract Neurol (2007) 10.1038/ncpneuro0426
[20]
Jacobi H "Inventory of non‐ataxia signs (INAS): validation of a new clinical assessment instrument" Cerebellum (2013) 10.1007/s12311-012-0421-3
[21]
De Leener B "SCT: spinal cord toolbox, an open‐source software for processing spinal cord MRI data" Neuroimage (2017) 10.1016/j.neuroimage.2016.10.009
[22]
Bédard S "Towards contrast‐agnostic soft segmentation of the spinal cord" Med Image Anal (2025) 10.1016/j.media.2025.103473
[23]
FSL

Mark Jenkinson, Christian F. Beckmann, Timothy E.J. Behrens et al.

NeuroImage 2012 10.1016/j.neuroimage.2011.09.015
[24]
Advances in functional and structural MR image analysis and implementation as FSL

Stephen M. Smith, Mark Jenkinson, Mark W. Woolrich et al.

NeuroImage 2004 10.1016/j.neuroimage.2004.07.051
[25]
De Leener B "PAM50: unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space" Neuroimage (2018) 10.1016/j.neuroimage.2017.10.041
[26]
Ullmann E "Automatic labeling of vertebral levels using a robust template‐based approach" Int J Biomed Imaging (2014)
[27]
Bédard S "Automatic measure and normalization of spinal cord cross‐sectional area using the pontomedullary junction" Front Neuroimaging (2022) 10.3389/fnimg.2022.1031253
[28]
FreeSurfer

Bruce Fischl

NeuroImage 2012 10.1016/j.neuroimage.2012.01.021
[29]
Iglesias JE "Bayesian segmentation of brainstem structures in MRI" Neuroimage (2015) 10.1016/j.neuroimage.2015.02.065
[30]
Faber J "CerebNet: a fast and reliable deep‐learning pipeline for detailed cerebellum sub‐segmentation" Neuroimage (2022) 10.1016/j.neuroimage.2022.119703
[31]
lmerTest Package: Tests in Linear Mixed Effects Models

Alexandra Kuznetsova, Per B. Brockhoff, Rune H. B. Christensen

Journal of Statistical Software 2017 10.18637/jss.v082.i13
[32]
Population Marginal Means in the Linear Model: An Alternative to Least Squares Means

S. R. Searle, F. M. Speed, G. A. Milliken

The American Statistician 1980 10.1080/00031305.1980.10483031
[33]
LenthRV.emmeans: Estimated Marginal Means aka Least‐Squares Means [Internet];2017. [cited 2025 Oct 28]. p. 1.11.2–8. Available from:https://CRAN.R-project.org/package=emmeans. 10.32614/cran.package.emmeans
[34]
Posit team (2025)
[35]
Prooije TH "The predictive validity of pontine volume change in spinocerebellar ataxia type 1 (SCA1)" Neurobiol Dis (2025) 10.1016/j.nbd.2025.107078
[36]
Rüb U "Damage to the reticulotegmental nucleus of the pons in spinocerebellar ataxia type 1, 2, and 3" Neurology (2004) 10.1212/01.wnl.0000140498.24112.8c
[37]
Robitaille Y "Structural and immunocytochemical features of olivopontocerebellar atrophy caused by the spinocerebellar ataxia type 1 (SCA‐1) mutation define a unique phenotype" Acta Neuropathol (Berl) (1995) 10.1007/bf00318569
[38]
Martins Junior CR "Structural signature in SCA1: clinical correlates, determinants and natural history" J Neurol (2018) 10.1007/s00415-018-9087-1
[39]
Rezende TJR "Progressive spinal cord degeneration in Friedreich's ataxia: results from ENIGMA‐ataxia" Mov Disord (2023) 10.1002/mds.29261
[40]
Baumeister H "Brain atrophy staging in spinocerebellar ataxia type 3 for clinical prognosis and trial enrichment" EBioMedicine (2026) 10.1016/j.ebiom.2025.106090
[41]
Rezende TJR "Value of MRI outcomes for preventive and early‐stage trials in spinocerebellar ataxias 1 and 3" Ann Clin Transl Neurol (2026) 10.1002/acn3.70325
[42]
Klockgether T "Spinocerebellar ataxia" Nat Rev Dis Primers (2019) 10.1038/s41572-019-0074-3
[43]
Kapteijns KCJ "The pattern and dynamics of white matter alterations in spinocerebellar ataxia type 1: a diffusion‐weighted magnetic resonance imaging study" Neuroimage Clin (2025) 10.1016/j.nicl.2025.103783
[44]
Tejwani L "Pathogenic mechanisms underlying spinocerebellar ataxia type 1" Cell Mol Life Sci (2020) 10.1007/s00018-020-03520-z
[45]
Paap BK "Standardized assessment of hereditary ataxia patients in clinical studies" Mov Disord Clin Pract (2016) 10.1002/mdc3.12315
[46]
Cohen Y "Diffusion MRI of the spinal cord: from structural studies to pathology" NMR Biomed (2017) 10.1002/nbm.3592
[47]
Taso M "A reliable spatially normalized template of the human spinal cord — applications to automated white matter/gray matter segmentation and tensor‐based morphometry (TBM) mapping of gray matter alterations occurring with age" Neuroimage (2015) 10.1016/j.neuroimage.2015.05.034
[48]
Gros C "Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks" Neuroimage (2019) 10.1016/j.neuroimage.2018.09.081
Metrics
0
Citations
48
References
Details
Published
Apr 09, 2026
License
View
Authors
Funding
Nederlandse Organisatie voor Wetenschappelijk Onderzoek Award: NWA.1389.20.244
Ministero della Salute Award: RF‐2011‐02347420
ZonMw Award: 40‐44600‐98‐606
Cite This Article
Colette J.M. Reniers, Teije H. van Prooije, Kirsten C.J. Kapteijns, et al. (2026). Early and Progressive Spinal Cord Atrophy in Spinocerebellar Ataxia Type 1. Movement Disorders. https://doi.org/10.1002/mds.70294