Cerebellar white matter integrity alterations in patients with Spinocerebellar Ataxia type 10
Poster No:
129
Submission Type:
Abstract Submission
Authors:
Allan Rico Becerra1, Miguel Hernandez Perez1, Angel Romero Molina1, Gabriel Ramirez Garcia1, Diana Torres Vences1, Erick Pasaye Alcaraz2, Juan Fernandez-Ruiz1
Institutions:
1Universidad Nacional Autónoma de México, Mexico City, Mexico, 2Instituto de Neurobiología-INB UNAM, Queretaro, Mexico
First Author:
Allan Rico Becerra, B.S. in Neuroscience
Universidad Nacional Autónoma de México
Mexico City, Mexico
Universidad Nacional Autónoma de México
Mexico City, Mexico
Co-Author(s):
Introduction:
Spinocerebellar ataxia type 10 (SCA10) is a neurodegenerative disease inherited in an autosomal dominant manner, characterized by cerebellar degeneration and symptoms such as gait ataxia, dysarthria, ocular movement abnormalities, and epileptic seizures (Ashizawa, 2012; Maatsura & Ashizawa, 2019). Additionally, cognitive deficits have been reported in individuals with SCA10 (Chirino-Perez et al., 2021). Despite these findings, knowledge regarding diffusion properties in the cerebellar white matter and their connection to motor and cognitive dysfunctions in SCA10 remains scarce.
Methods:
Twelve patients diagnosed with SCA10 and eight healthy controls (Ctrl) were recruited for this study. Both groups were matched for gender, age, and years of education. All participants underwent magnetic resonance imaging (MRI), which included diffusion-weighted imaging (b=2500, 60 directions) and T1-weighted structural imaging. Diffusion-weighted images were preprocessed using MRtrix3.0 software, following the pipeline proposed by Tournier et al. (2019) and Jahn (2022). Diffusion tensor imaging (DTI) metrics, including fractional anisotropy (FA), apparent diffusion coefficient (ADC), radial diffusivity (RD), and axial diffusivity (AD) of the cerebellar white matter, were subsequently calculated.
To assess disease severity, participants underwent motor and cognitive evaluations. Motor symptoms were assessed using the Scale for the Assessment and Rating of Ataxia (SARA), while cognitive functions were screened using the Montreal Cognitive Assessment (MoCA) and the Cerebellar Cognitive Affective Syndrome Scale (CCAS).
The Shapiro-Wilk test was applied to assess the normality of all measures. Between-group comparisons were conducted using independent t-tests and effect size was calculated for each comparison with Cohen's d. Additionally, Pearson correlation coefficients were calculated to explore relationships between DTI metrics and motor as well as cognitive screening scores in the SCA10 group. Statistical significance was set at p<0.05. To control the false discovery rate (FDR), p-values were adjusted using the Benjamini-Hochberg procedure with a Q-value of 0.05.
To assess disease severity, participants underwent motor and cognitive evaluations. Motor symptoms were assessed using the Scale for the Assessment and Rating of Ataxia (SARA), while cognitive functions were screened using the Montreal Cognitive Assessment (MoCA) and the Cerebellar Cognitive Affective Syndrome Scale (CCAS).
The Shapiro-Wilk test was applied to assess the normality of all measures. Between-group comparisons were conducted using independent t-tests and effect size was calculated for each comparison with Cohen's d. Additionally, Pearson correlation coefficients were calculated to explore relationships between DTI metrics and motor as well as cognitive screening scores in the SCA10 group. Statistical significance was set at p<0.05. To control the false discovery rate (FDR), p-values were adjusted using the Benjamini-Hochberg procedure with a Q-value of 0.05.
Results:
In cognitive screening, SCA10 patients exhibited lower scores compared to the Ctrl group, as assessed by both the MoCA (t=2.104, p=0.025, d=-1.01) and CCAS (t=2.925, p=0.004, d=-1.41) tests. Regarding DTI metrics in cerebellar white matter, SCA10 patients showed higher values of ADC (t=3.399, p=0.004, d=1.62) and RD (t=2.608, p=0.01, d=1.24) (Figure 1A,B); however, no significant differences were observed between SCA10 and the Ctrl group in FA (t=0.358, p=0.362, d=-0.17) or AD (t=1.022, p=0.213, d=0.48) metrics.
The ADC and RD metrics demonstrated significant positive correlations with SARA scores (r=0.72, p=0.01; r=0.70, p=0.01, respectively), whereas no significant correlations were found for FA (r=-0.43, p=0.07) or AD (r=0.49, p=0.06) (Figure 2). Additionally, none of the DTI metrics showed significant correlations with any cognitive screening scores.
The ADC and RD metrics demonstrated significant positive correlations with SARA scores (r=0.72, p=0.01; r=0.70, p=0.01, respectively), whereas no significant correlations were found for FA (r=-0.43, p=0.07) or AD (r=0.49, p=0.06) (Figure 2). Additionally, none of the DTI metrics showed significant correlations with any cognitive screening scores.
·Figure 1. Between group comparisons in ADC and RD
·Figure 2. Correlation analyses between DTI metrics and SARA scores in SCA10 group
Conclusions:
The present findings suggest alterations in cerebellar white matter integrity in patients diagnosed with SCA10. Notably, these changes appear to impact water diffusion in the direction perpendicular to the primary diffusion axis, potentially reflecting demyelination processes. Furthermore, these cerebellar white matter alterations are positively associated with the severity of motor symptoms in SCA10. This study offers novel and significant insights into SCA10, including its symptomatology and white matter integrity alterations.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Novel Imaging Acquisition Methods:
Diffusion MRI 2
Keywords:
Cerebellum
Degenerative Disease
MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Other - Spinocerebellar ataxia type 10
1|2Indicates the priority used for review
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Provide references using APA citation style.
Chirino-Pérez, A., Vaca-Palomares, I., Torres, D. L., Hernandez-Castillo, C. R., Diaz, R., Ramirez-Garcia, G., & Fernandez-Ruiz, J. (2021). Cognitive Impairments in Spinocerebellar Ataxia Type 10 and Their Relation to Cortical Thickness. Movement Disorders, 36(12), 2910–2921. https://doi.org/10.1002/mds.28728
Jahn, A. (2022). MRtrix Tutorial #4: Preprocessing - Andy’s Brain Book 1.0 documentation. https://andysbrainbook.readthedocs.io/en/latest/MRtrix/MRtrix_Course/MRtrix_04_Preprocessing.html
Matsuura, T., & Ashizawa, T. (2019, September 19). Spinocerebellar Ataxia Type 10. GeneReviews [Internet]. https://www.ncbi.nlm.nih.gov/books/NBK1175/
Tournier, J., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C., & Connelly, A. (2019). MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation. NeuroImage, 202, 116137. https://doi.org/10.1016/j.neuroimage.2019.116137