Solving the Etiology of Developmental and Epileptic Encephalopathy with Spike-Wave Activation in Sleep (D/EE-SWAS)

Abstract

Objective: To understand the etiological landscape and phenotypic differences between 2 developmental and epileptic encephalopathy (DEE) syndromes: DEE with spike-wave activation in sleep (DEE-SWAS) and epileptic encephalopathy with spike-wave activation in sleep (EE-SWAS).

Methods: All patients fulfilled International League Against Epilepsy (ILAE) DEE-SWAS or EE-SWAS criteria with a Core cohort (n = 91) drawn from our Epilepsy Genetics research program, together with 10 etiologically solved patients referred by collaborators in the Expanded cohort (n = 101). Detailed phenotyping and analysis of molecular genetic results were performed. We compared the phenotypic features of individuals with DEE-SWAS and EE-SWAS. Brain-specific gene co-expression analysis was performed for D/EE-SWAS genes.

Results: We identified the etiology in 42/91 (46%) patients in our Core cohort, including 29/44 (66%) with DEE-SWAS and 13/47 (28%) with EE-SWAS. A genetic etiology was identified in 31/91 (34%). D/EE-SWAS genes were highly co-expressed in brain, highlighting the importance of channelopathies and transcriptional regulators. Structural etiologies were found in 12/91 (13%) individuals. We identified 10 novel D/EE-SWAS genes with a range of functions: ATP1A2, CACNA1A, FOXP1, GRIN1, KCNMA1, KCNQ3, PPFIA3, PUF60, SETD1B, and ZBTB18, and 2 novel copy number variants, 17p11.2 duplication and 5q22 deletion. Although developmental regression patterns were similar in both syndromes, DEE-SWAS was associated with a longer duration of epilepsy and poorer intellectual outcome than EE-SWAS.

Interpretation: DEE-SWAS and EE-SWAS have highly heterogeneous genetic and structural etiologies. Phenotypic analysis highlights valuable clinical differences between DEE-SWAS and EE-SWAS which inform clinical care and prognostic counseling. Our etiological findings pave the way for the development of precision therapies. ANN NEUROL 2024;96:932-943.

Figure 1:

Seizure types in DEE-SWAS and EE-SWAS

Figure 2:

(A) Developmental regression by domain (speech and language, cognitive, behaviour and motor) in individuals with DEE-SWAS and EE-SWAS, (B) Intellectual outcome in patients with DEE-SWAS and EE-SWAS

Figure 3:

(A) Probability of time to seizure remission (n=93) (B) Probability of time to SWAS remission (n=101). Probability was calculated using the Kaplan–Meier method for survival analysis. The shaded colour regions define the 95% confidence intervals. Coloured vertical dashes along each survival curve denote the most recent age of individuals known to still be experiencing seizures or SWAS (B) (censored observations). Median time to event (seizure or SWAS offset) for each group indicated by black dashed lines.

Figure 4:

Epilepsy syndromic terminology and evolution (A) Mapping of old ILAE terminology of epilepsy syndromes diagnosed in patients with the epilepsy-aphasia spectrum (Landau-Kleffner syndrome, Encephalopathy with Continuous Spike-Wave in Sleep, Atypical Benign Focal Epilepsy of Childhood, Unclassified) to 2022 ILAE terminology of DEE-SWAS and EE-SWAS, (B) Evolution from DEE-SWAS to Lennox-Gastaut syndrome in 3 probands(SWAS, spike-wave activation in sleep; GPFA, generalised paroxysmal fast activity

Figure 5:

Solved cases in our Core cohort, n=91, by etiology and epilepsy syndromes.

Figure 6:

Genetic findings in patients with DEE-SWAS and EE-SWAS in the Expanded cohort highlighting functional roles.

Figure 7:

Gene co-expression matrix for 20 DEE-SWAS and EE-SWAS genes. Pairwise Spearman correlations between genes shown, based on 524 samples from 42 individuals from the BrainSpan resource. Genes are ordered and grouped with hierarchical clustering, using the median linkage method. Black boxes denote clusters of highly correlated genes (top left box for cluster 1 and bottom right box for cluster 2).