A resting-state fMRI pattern of spinocerebellar ataxia type 3 and comparison with F-18-FDG PET

Harm J van der Horn*, Sanne K Meles, Jelmer G Kok, Victor M Vergara, Shile Qi, Vince D Calhoun, Jelle R Dalenberg, Jeroen C W Siero, Remco J Renken, Jeroen J de Vries, Jacoba M Spikman, Hubertus P H Kremer, Bauke M De Jong

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Spinocerebellar ataxia type 3 (SCA3) is a rare genetic neurodegenerative disease. The neurobiological basis of SCA3 is still poorly understood, and up until now resting-state fMRI (rs-fMRI) has not been used to study this disease. In the current study we investigated (multi-echo) rs-fMRI data from patients with genetically confirmed SCA3 (n = 17) and matched healthy subjects (n = 16). Using independent component analysis (ICA) and subsequent regression with bootstrap resampling, we identified a pattern of differences between patients and healthy subjects, which we coined the fMRI SCA3 related pattern (fSCA3-RP) comprising cerebellum, anterior striatum and various cortical regions. Individual fSCA3-RP scores were highly correlated with a previously published F-18-FDG PET pattern found in the same sample (rho = 0.78, P = 0.0003). Also, a high correlation was found with the Scale for Assessment and Rating of Ataxia scores (r = 0.63, P = 0.007). No correlations were found with neuropsychological test scores, nor with levels of grey matter atrophy. Compared with the F-18-FDG PET pattern, the fSCA3-RP included a more extensive contribution of the mediofrontal cortex, putatively representing changes in default network activity. This rs-fMRI identification of additional regions is proposed to reflect a consequence of the nature of the BOLD technique, enabling measurement of dynamic network activity, compared to the more static F-18-FDG PET methodology. Altogether, our findings shed new light on the neural substrate of SCA3, and encourage further validation of the fSCA3-RP to assess its potential contribution as imaging biomarker for future research and clinical use.

Original languageEnglish
Article number103023
Number of pages10
JournalNeuroImage. Clinical
Publication statusPublished - 25-Apr-2022


  • BOLD
  • Ataxia
  • ICA
  • Brain glucose metabolism
  • Disease-related pattern


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