Shift in interictal relative gamma power as a novel biomarker for drug response in two mouse models of absence epilepsy

Two monogenic mouse models of childhood absence epilepsy, stargazer and tottering, differ strikingly in their response to N-methyl-d-aspartate (NMDA) receptor blockade. We sought to evaluate the change in interictal relative gamma power as a reliable biomarker for this gene-linked antiepileptic drug (AED) response.

The effects of AEDs on absolute and relative (to the total) power of frequencies between 2 and 300 Hz were analyzed within the interictal electroencephalogram (EEG) and correlated with antiseizure efficacy in awake behaving stargazer, tottering, and wild-type (WT) littermate control mice.

At baseline, we found a significant absolute as well as relative augmentation of 16-41 Hz power in stargazer compared to both tottering and WT mice. In stargazer, the NMDA receptor-antagonist MK-801 (0.5 mg/kg) paradoxically exacerbates absence seizures but normalizes the augmented beta/gamma band of power to WT levels, suggesting that the elevation in 16- to 41-Hz power is an NMDA receptor-mediated network property. In contrast, ethosuximide (200 mg/kg) and 4-aminopyridine (2.5 mg/kg) reduce seizure activity and increase relative power within the gamma range in both stargazer and tottering mice. Intraperitoneal saline injection had no significant effect on either seizure frequency or relative gamma power. Along with results using carbamazepine and flupirtine, there was a strong inverse relationship between relative change in seizure duration and change in peak relative gamma power (r(2) = 0.726).

In these two models of absence epilepsy, drugs that reduce relative gamma power are associated with an increase in seizures, whereas drugs that augment relative gamma power reduce seizures. Therefore, drug-induced modulation of relative gamma power may serve as a biomarker for AED efficacy in absence epilepsy. Given the relationship between gamma power and fast-spiking interneurons, these results also suggest that a drug's effect may in part be determined by its impact on specific inhibitory networks.