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

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Abstract

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 18F-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 18F-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 18F-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
Pages (from-to)1-10
JournalNeuroImage: Clinical
Volume34
DOIs
Publication statusPublished - 2022

Keywords

  • Ataxia
  • BOLD
  • Brain glucose metabolism
  • Disease-related pattern
  • ICA
  • Neurodegenerative Diseases
  • Machado-Joseph Disease/diagnostic imaging
  • Humans
  • Fluorodeoxyglucose F18
  • Magnetic Resonance Imaging/methods
  • Positron-Emission Tomography/methods

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