Combined electrophysiological and morphological phenotypes in patients with genetic generalized epilepsy and their healthy siblings

Abstract

Abstract

Objective Genetic generalized epilepsy (GGE) is characterized by aberrant neuronal dynamics and subtle structural alterations. We evaluated whether a combination of magnetic and electrical neuronal signals and cortical thickness would provide complementary information about network pathology in GGE. We also investigated whether these imaging phenotypes were present in healthy siblings of the patients to test for genetic influence.

Methods In this cross‐sectional study, we analyzed 5 min of resting state data acquired using electroencephalography (EEG) and magnetoencephalography (MEG) in patients, their siblings, and controls, matched for age and sex. We computed source‐reconstructed power and connectivity in six frequency bands (1–40 Hz) and cortical thickness (derived from magnetic resonance imaging). Group differences were assessed using permutation analysis of linear models for each modality separately and jointly for all modalities using a nonparametric combination.

Results Patients with GGE (n = 23) had higher power than controls (n = 35) in all frequencies, with a more posterior focus in MEG than EEG. Connectivity was also increased, particularly in frontotemporal and central regions in theta (strongest in EEG) and low beta frequencies (strongest in MEG), which was eminent in the joint EEG/MEG analysis. EEG showed weaker connectivity differences in higher frequencies, possibly related to drug effects. The inclusion of cortical thickness reinforced group differences in connectivity and power. Siblings (n = 18) had functional and structural patterns intermediate between those of patients and controls.

Significance EEG detected increased connectivity and power in GGE similar to MEG, but with different spectral sensitivity, highlighting the importance of theta and beta oscillations. Cortical thickness reductions in GGE corresponded to functional imaging patterns. Our multimodal approach extends the understanding of the resting state in GGE and points to genetic underpinnings of the imaging markers studied, providing new insights into the causes and consequences of epilepsy.