Pointed rhythmic theta waves: a unique EEG pattern in KCNQ2-related neonatal epileptic encephalopathy

KCNQ2-Related Epilepsy: Genotype-Phenotype Relationship with Tailored Antiseizure Medication (ASM)-A Systematic Review

BACKGROUND

Autosomal dominant mutations of the KCNQ2 gene can cause two epileptic disorders: benign familial neonatal seizures (BFNS) and developmental epileptic encephalopathy (DEE). This systematic review aims to identify the best reported therapy for these patients, relating to phenotype, neurodevelopmental outcome, and an eventual correlation between phenotype and genotype.

METHODS

We searched on PubMed using the search terms "KCNQ2" AND "therapy" and "KCNQ2" AND "treatment"; we found 304 articles. Of these, 29 met our criteria. We collected the data from 194 patients. All 29 articles were retrospective studies.

RESULTS

In all, 104 patients were classified as DEE and 90 as BFNS. After treatment began, 95% of BFNS patients became seizure free, whereas the seizures stopped only in 73% of those with DEE. Phenobarbital and sodium channel blockers were the most used treatment in BFNS. Most of the DEE patients (95%) needed polytherapy for seizure control and even that did not prevent subsequent developmental impairment (77%).Missense mutations were discovered in 96% of DEE patients; these were less common in BFNS (50%), followed by large deletion (16%), truncation (16%), splice donor site (10%), and frameshift (7%).

CONCLUSION

Phenobarbital or carbamazepine appears to be the most effective antiseizure medication for children with a "benign" variant. On the contrary, polytherapy is often needed for DEE patients, even if it does not seem to improve neurological outcomes. In DEE patients, most mutations were located in S4 and S6 helix, which could serve as a potential target for the development of more specific treatment in the future.

Prognostic Analysis of KCNQ2 Patients via Combining EEG Deep Features and Machine Learning Classifiers

Pathogenic variants of the KCNQ2 gene often induces neonatal epilepsy in clinical. For better treatment, infants with confirmed KCNQ2 pathogenic variant and epilepsy symptoms need to adjust their treatment plans according to the outcome after taking antiseizure medicines (ASMs). This process is often time-consuming and requires long-term follow-up, which undoubtedly causes unnecessary psychological and economic burdens. In this study, we investigate the feasibility to predict the outcome of KCNQ2 patients via Electroencephalogram (EEG). By using the combination of deep networks and classical classifiers, the abnormal brain pathological activities recorded in EEGs can be encoded into deep features and decoded into specific KCNQ2 outcomes, thus taking the advantage of both powerful feature extraction capability from deep networks and stronger classification ability from classical classifiers. Specifically, we acquire 10-channel EEG signals from 33 infants with KCNQ2 pathogenic variants after taking ASMs. Two well-trained models (Resnet-50 and Resnet-18) are employed to extract deep features from the EEG spectrums. We achieve an accuracy of 78.7% to predict the KCNQ2 outcome of each infant. To our best knowledge, this is the first study to employ potential EEG pathological differences to predict the outcomes of KCNQ2 patients. The investigation of automatic KCNQ2 outcome prediction may contribute to a more convenient diagnosis mechanism for KCNQ2 patients.

Treating the symptom or treating the disease in neonatal seizures: a systematic review of the literature

Aim

The existing treatment options for neonatal seizures have expanded over the last few decades, but no consensus has been reached regarding the optimal therapeutic protocols. We systematically reviewed the available literature examining neonatal seizure treatments to clarify which drugs are the most effective for the treatment of specific neurologic disorders in newborns.

Method

We reviewed all available, published, literature, identified using PubMed (published between August 1949 and November 2020), that focused on the pharmacological treatment of electroencephalogram (EEG)-confirmed neonatal seizures.

Results

Our search identified 427 articles, of which 67 were included in this review. Current knowledge allowed us to highlight the good clinical and electrographic responses of genetic early-onset epilepsies to sodium channel blockers and the overall good response to levetiracetam, whose administration has also been demonstrated to be safe in both full-term and preterm newborns.

Interpretation

Our work contributes by confirming the limited availability of evidence that can be used to guide the use of anticonvulsants to treat newborns in clinical practice and examining the efficacy and potentially harmful side effects of currently available drugs when used to treat the developing newborn brain; therefore, our work might also serve as a clinical reference for future studies.

Ictal and interictal electroencephalographic findings can contribute to early diagnosis and prompt treatment in KCNQ2-associated epileptic encephalopathy

BACKGROUND

KCNQ2-associated epilepsy is most common in neonatal genetic epilepsy. A prompt diagnosis to initialize early treatment is important.

METHODS

We studied the electroencephalographic (EEG) changes including automated EEGs and conventional EEGs monitoring of 10 nonconsanguineous cases with KCNQ2 mutations, identified among 162 (6%) childhood epilepsy. We compared 11 (25%) non-KCNQ2 seizures videoed from 44 automated EEG and EEG monitoring.

RESULTS

Patients with KCNQ2 seizures had received more antiepileptic treatments than patients in non-KCNQ2 group. Seizures were detected in all patients with KCNQ2 epileptic encephalopathy (EE); the detection rate in KCNQ2 group was more than in patients with non-KCNQ2. The ictal recordings showed 3 newborns presented with initial lower amplitudes (<15 μV) and fast activity (>20 Hz), evolving into higher-amplitude theta-delta waves. Two patient's ictal seizures showed recurrent focal tonic movements of the unilateral limbs associated with slowly continuous spikes in the contralateral hemisphere. The interictal EEGs in 5 KCNQ2 EE were burst-suppression. In 5 patients with familial KCNQ2 mutations, the interictal EEGs showed focal paroxysmal activity. Compared with 11 non-KCNQ2 EEG of ictal seizures, the differences are ictal EEGs initially appeared manifesting theta-delta waves without fast activities. In KCNQ2 seizures, patients with mutations locating in the selectivity filter controlling K⁺ permeability had severe EEG patterns and poor neurodevelopmental outcomes.

CONCLUSION

Ictal EEGs in KCNQ2 seizures are unique and different from the EEGs of seizures with other etiologies. An EEG monitoring can be a valuable tool for early diagnosing KCNQ2-associated seizures and for supporting prompt treatments.