Resting-State EEG Analysis Characterizes the Signature of CACNA1A-and GAA-FGF14-Related Channelopathies

Area of Science:

• Neuroscience
• Genetics
• Medical Imaging

Background:

• Cerebellar ataxia often stems from ion channel dysfunction, with CACNA1A and GAA-FGF14 gene-related diseases being common genetic causes.
• While clinically similar, the underlying pathophysiology of these channelopathies is distinct and not fully understood.
• Advanced resting-state electroencephalogram (rsEEG) analysis is a powerful tool for evaluating brain network dynamics.

Purpose of the Study:

• To differentiate electrophysiological patterns in CACNA1A-related disease and GAA-FGF14-related disease using advanced rsEEG analysis.
• To identify disease-specific biomarkers for these rare channelopathies.
• To correlate EEG findings with clinical presentations.

Main Methods:

• Retrospective collection of scalp EEG data from genetically confirmed CACNA1A (n=29) and GAA-FGF14 (n=15) patients and healthy controls.
• Application of advanced rsEEG analysis, including Bayesian hierarchical modeling, to assess spectral bandpower and functional connectivity.
• Analysis of EEG data across different frequency bands (delta, theta, alpha, beta, gamma).

Main Results:

• CACNA1A patients exhibited significantly increased theta-band power, reduced alpha peak frequency, and enhanced delta/theta and gamma functional connectivity compared to controls.
• GAA-FGF14 patients showed minimal differences from controls, with only mild increases in beta power and alpha band hyperconnectivity.
• These distinct patterns align with the observed clinical differences: widespread network dysfunction in CACNA1A disease versus a predominantly motor presentation in GAA-FGF14 disease.

Conclusions:

• Advanced rsEEG analysis can detect and quantify disease-specific electrophysiological alterations in rare channelopathies.
• The findings suggest potential for rsEEG-derived surrogate markers in diagnosing and monitoring CACNA1A-related and GAA-FGF14-related cerebellar ataxias.
• The distinct network profiles support the differing clinical manifestations of these genetic disorders.