Electrophysiological Biomarkers in Genetic Epilepsies

The regulatory function of lncRNA and constructed network in epilepsy

BACKGROUND

Epilepsy is a neurological disease characterized by neural network dysfunction. Although most reports indicate that the pathological process of epilepsy is related to inflammation, synaptic plasticity, cell apoptosis, and ion channel dysfunction, the underlying molecular mechanisms of epilepsy are not fully understood.

METHODS

This review summarizes the latest literature on the roles and characteristics of long noncoding RNAs (lncRNAs) in the pathogenesis of epilepsy.

RESULTS

lncRNAs are a class of long transcripts without protein-coding functions that perform important regulatory functions in various biological processes. lncRNAs are involved in the regulation of the pathological process of epilepsy and are abnormally expressed in both patients and animal models. This review provides an overview of research progress in epilepsy, the multifunctional features of lncRNAs, the lncRNA expression pattern related to epileptogenesis and status epilepticus, and the potential mechanisms for the two interactions contributing to epileptogenesis and progression.

CONCLUSION

lncRNAs can serve as new diagnostic markers and therapeutic targets for epilepsy in the future.

Quantitative electroencephalographic analysis as a potential biomarker of response to treatment with cannabidiol

PURPOSE

Pharmaceutical grade cannabidiol (CBD) is one of the newest anti-seizure medications for refractory epilepsy, and the effects of CBD on EEG have not been fully described.

METHODS

Patients enrolled in a CBD expanded access study had EEGs prior to and 12 weeks after initiation of CBD treatment for their refractory epilepsy. In addition to evaluating the clinical EEG reports, a nonbiased quantitative EEG (qEEG) analysis of background EEG was performed to determine whether consistent changes occur in the EEG in response to administration of CBD.

RESULTS

No significant qualitative changes were seen, nor changes in quantitative markers of EEG amplitude (RMS amplitude, standard deviation of the amplitude, skewness, or kurtosis), frequency (relative delta, theta, or alpha power), Spearman correlation, or coherence between brain regions. However, relative beta power and 1/f slope, a measure of signal noise increased with the addition of CBD. When patients were separated into responders and nonresponders based on seizure reduction with CBD, responders also had decreased Spearman correlation between the frontopolar and occipital regions after addition of CBD, suggesting that responders may have quantitatively improved EEG background organization after CBD initiation. The differences in beta and 1/f slope were also seen more robustly in CBD responders compared with nonresponders after CBD initiation. These differences disappeared when analyzing only patients not taking benzodiazepines, suggesting that the effect of CBD on seizures was related to the ability of the brain to further increase beta in response to CBD in patients already taking benzodiazepines. We noted that even before initiation of CBD, 1/f slope was also significantly different in responders compared to nonresponders. Therefore, to explore the baseline EEG in responders and nonresponders, we utilized a variable selection procedure to identify baseline EEG features that could predict whether a patient's seizures would improve with CBD. In the optimal multivariable logistic model, baseline coherence, Spearman correlation, and patient sex jointly predicted whether a patient in this cohort would respond to CBD (defined as a seizure reduction of 40% or greater) with 74% accuracy. This model performed less well on a data set of reduced duration and variability, highlighting the importance of real-world testing of any clinically relevant model.

CONCLUSION

These results suggest that there are subtle changes in certain metrics detected by qEEG even at baseline that may not be perceived during qualitative EEG analysis and that could be used in the future as a biomarker to predict a patient's clinical response to CBD administration. Development of such a predictive EEG biomarker, especially before the initiation of a medication trial, could reduce unnecessary ASM exposure and improve outcomes for patients with epilepsy facing new medication selection.