Neuronal oscillatory imbalances in GNAO1-related disorders associated with disease severity.

OBJECTIVE

This study investigates excitatory/inhibitory (E/I) imbalances in GNAO1-related disorders (GNAO1-RD), linking neuronal dysfunction to clinical severity using E/I-sensitive electroencephalography (EEG) analyses.

METHODS

We conducted an observational study involving 12 children with GNAO1-RD caused by pathogenic variants and 36 age-matched, typically developing children (TDC). EEG was recorded during eyes-closed rest. Clinical evaluations included scales for epilepsy, movement disorders, motor and language development, and an overall clinical severity score. Molecular assessments of GNAO1 variants used bioluminescence resonance energy transfer (BRET) assays. Quantitative EEG measures included spectral power, aperiodic exponent, long-range temporal correlations (LRTCs), and functional E/I (fE/I) ratio. Statistical analyses incorporated permutation tests and cluster-based enhancements.

RESULTS

Children with GNAO1-RD exhibited elevated delta power and reduced alpha power compared to TDC. Higher delta power correlated with more severe epilepsy and pronounced molecular dysfunction, whereas lower alpha power was associated with overall clinical severity. Stronger alpha- and beta-band LRTCs were observed in GNAO1-RD, reflecting altered network dynamics. Reduced alpha-band fE/I ratios suggested a network state dominated by inhibition, potentially compensating for hyperexcitability. Developmental differences were evident, as the age-related decreases in delta power observed in TDCs were absent in GNAO1-RD.

SIGNIFICANCE

This study identifies quantitative EEG abnormalities in GNAO1-RD, characterized by increased delta power, decreased alpha power, and disrupted network dynamics indicative of an inhibition-dominant state. These findings align with molecular dysfunction caused by GNAO1 variants, highlighting the role of GNAO1 in maintaining E/I balance. The results provide neurophysiological insights into GNAO1-RD pathophysiology and suggest potential biomarkers for assessing disease severity and therapeutic interventions.