NEXMIF encephalopathy: an X-linked disorder with male and female phenotypic patterns

PURPOSE

Pathogenic variants in the X-linked gene NEXMIF (previously KIAA2022) are associated with intellectual disability (ID), autism spectrum disorder, and epilepsy. We aimed to delineate the female and male phenotypic spectrum of NEXMIF encephalopathy.

METHODS

Through an international collaboration, we analyzed the phenotypes and genotypes of 87 patients with NEXMIF encephalopathy.

RESULTS

Sixty-three females and 24 males (46 new patients) with NEXMIF encephalopathy were studied, with 30 novel variants. Phenotypic features included developmental delay/ID in 86/87 (99%), seizures in 71/86 (83%) and multiple comorbidities. Generalized seizures predominated including myoclonic seizures and absence seizures (both 46/70, 66%), absence with eyelid myoclonia (17/70, 24%), and atonic seizures (30/70, 43%). Males had more severe developmental impairment; females had epilepsy more frequently, and varied from unaffected to severely affected. All NEXMIF pathogenic variants led to a premature stop codon or were deleterious structural variants. Most arose de novo, although X-linked segregation occurred for both sexes. Somatic mosaicism occurred in two males and a family with suspected parental mosaicism.

CONCLUSION

NEXMIF encephalopathy is an X-linked, generalized developmental and epileptic encephalopathy characterized by myoclonic-atonic epilepsy overlapping with eyelid myoclonia with absence. Some patients have developmental encephalopathy without epilepsy. Males have more severe developmental impairment. NEXMIF encephalopathy arises due to loss-of-function variants.

A Framework to Assess the Information Dynamics of Source EEG Activity and Its Application to Epileptic Brain Networks

This study introduces a framework for the information-theoretic analysis of brain functional connectivity performed at the level of electroencephalogram (EEG) sources. The framework combines the use of common spatial patterns to select the EEG components which maximize the variance between two experimental conditions, simultaneous implementation of vector autoregressive modeling (VAR) with independent component analysis to describe the joint source dynamics and their projection to the scalp, and computation of information dynamics measures (information storage, information transfer, statistically significant network links) from the source VAR parameters. The proposed framework was tested on simulated EEGs obtained mixing source signals generated under different coupling conditions, showing its ability to retrieve source information dynamics from the scalp signals. Then, it was applied to investigate scalp and source brain connectivity in a group of children manifesting episodes of focal and generalized epilepsy; the analysis was performed on EEG signals lasting 5 s, collected in two consecutive windows preceding and one window following each ictal episode. Our results show that generalized seizures are associated with a significant decrease from pre-ictal to post-ictal periods of the information stored in the signals and of the information transferred among them, reflecting reduced self-predictability and causal connectivity at the level of both scalp and source brain dynamics. On the contrary, in the case of focal seizures the scalp EEG activity was not discriminated across conditions by any information measure, while source analysis revealed a tendency of the measures of information transfer to increase just before seizures and to decrease just after seizures. These results suggest that focal epileptic seizures are associated with a reorganization of the topology of EEG brain networks which is only visible analyzing connectivity among the brain sources. Our findings emphasize the importance of EEG modeling approaches able to deal with the adverse effects of volume conduction on brain connectivity analysis, and their potential relevance to the development of strategies for prediction and clinical treatment of epilepsy.

Are Epileptic Spasms a Seizure Type for the Insular Region?

Two patients with insular and striatal postnatal scar had epileptic spasms (ES) that were asymmetrical and the only seizure type, whereas none of the usual ictal symptoms of insular seizures occurred. Ictal electroencephalography (EEG) showed the high-amplitude slow-wave characteristic of ES. Vigabatrin remained efficient for over 4 years for one patient and right into the third decade for the other one. Such ES are distinct from infantile and late onset spasms. Furthermore, these observations suggest that in ES insular epilepsy triggers paroxysmal activation of the striatum, and that vigabatrin inhibits the striatal startle motor program, thus interrupting the corticostriatal loop.

Time, frequency and information domain analysis of short-term heart rate variability before and after focal and generalized seizures in epileptic children

OBJECTIVE

In this work we explore the potential of combining standard time and frequency domain indexes with novel information measures, to characterize pre- and post-ictal heart rate variability (HRV) in epileptic children, with the aim of differentiating focal and generalized epilepsy regarding the autonomic control mechanisms.

APPROACH

We analyze short-term HRV in 37 children suffering from generalized or focal epilepsy, monitored 10 s, 300 s, 600 s and 1800 s both before and after seizure episodes. Nine indexes are computed in time (mean, standard deviation of normal-to-normal intervals, root mean square of the successive differences (RMSSD)), frequency (low-to-high frequency power ratio LF/HF, normalized LF and HF power) and information (entropy, conditional entropy and self-entropy) domains. Focal and generalized epilepsy are compared through statistical analysis of the indexes and using linear discriminant analysis (LDA).

MAIN RESULTS

In children with focal epilepsy, early post-ictal phase is characterized by significant tachycardia, depressed HRV, increased LF power and LF/HF, and decreased complexity, progressively recovered across time windows after the episodes. Children with generalized seizures instead show significant tachycardia, lower RMSSD, higher LF power and LF/HF ratio before the seizure. These different behaviors are exploited by LDA analysis to separate focal and generalized epilepsy up to an accuracy of 75%. Results suggest a shift of the sympatho-vagal balance towards sympathetic dominance and vagal withdrawal, noticeable just after the termination of seizure episodes and then reverted in focal epilepsy, and persistent during inter-ictal and pre-ictal periods in generalized epilepsy.

SIGNIFICANCE

Our analysis helps in elucidating the pathophysiology of inter-ictal HRV autonomic control and the differential diagnosis of generalized and focal epilepsy. These findings may have clinical relevance since altered sympatho-vagal control can be related to a higher danger of morbidity and mortality, may reduce thresholds for life-threatening arrhythmias, and could be a biomarker of risk for sudden unexpected death in epilepsy.