Objective: To assess cerebellar volumetry using a deep learning method in patients with non-polyglutamine CACNA1A- or GAA-FGF14-related disease.

Background: Ion channel dysfunction is a recurring etiology in inherited ataxias. Ataxic syndromes associated to channelopathies typically present with both chronic and episodic neurological symptoms and usually show an exclusive or prevalent involvement of the vermis in imaging studies. These features are recapitulated by CACNA1A and FGF14 related disorders, which list among the most frequent molecular etiologies of inherited ataxias.

Method: 3-dimensional T1‐weighted images from 3.0 Tesla MRI acquisition were processed with FastSurfer and the CerebNet module to segment subcortical brain region. Normative data for subcortical regional volumes over the lifetime of the adult human brain were generated from healthy participants from open access MR datasets. After z-transformation, a k-means clustering analysis with 3 centers was performed to group the data points into distinct clusters based on their similarity, aiming to identify underlying patterns of infratentorial brain atrophy. Subsequently, a principal components analysis (PCA) of the cluster dimensions was conducted to study what dimensions primarily drive cluster separation.

Results: In the cluster analysis, Cluster 1 contains 6 patients carrying missense CACNA1A variants who had an early onset of disease (Age 7, range 1-12 years) and present with hemiplegic migraine as episodic feature (p=0.004). Patients in cluster 2 (n=16), and cluster 3 (n=6) presented mixed genotypes, but an increasing frequency of episodic ataxia as paroxysmal manifestation (p=0.028) and an increasing age at onset (p=0.01) were observed from cluster 1 to cluster 3. The PCA revealed that already 2 principal components account for 83% of the total variance in the dataset with the first principal component explaining 78% of the variance indicating that it captures the most significant patterns. Vermis atrophy and the cerebellar lobules IV–VII had the highest contribution to this principal component. Cerebellar volume loss did not correlate with the age at the examination nor with the severity of the chronic cerebellar syndrome as expressed by clinical scores.

Conclusion: Age at onset and the molecular mechanism of channel dysfunction are the key determinant of cerebellar volume loss in CACNA1A and GAA-FGF14-disease.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/genotype-and-age-at-onset-drive-vermis-atrophy-in-cacna1a-and-gaa-fgf14-related-ataxias/