Developmental epileptic encephalopathy in DLG4-related synaptopathy.

OBJECTIVE: The postsynaptic density protein of excitatory neurons PSD-95 is encoded by discs large MAGUK scaffold protein 4 (DLG4), de novo pathogenic variants of which lead to DLG4-related synaptopathy. The major clinical features are developmental delay, intellectual disability (ID), hypotonia, sleep disturbances, movement disorders, and epilepsy. Even though epilepsy is present in 50% of the individuals, it has not been investigated in detail. We describe here the phenotypic spectrum of epilepsy and associated comorbidities in patients with DLG4-related synaptopathy. METHODS: We included 35 individuals with a DLG4 variant and epilepsy as part of a multicenter study. The DLG4 variants were detected by the referring laboratories. The degree of ID, hypotonia, developmental delay, and motor disturbances were evaluated by the referring clinician. Data on awake and sleep electroencephalography (EEG) and/or video-polygraphy and brain magnetic resonance imaging were collected. Antiseizure medication response was retrospectively assessed by the referring clinician. RESULTS: A large variety of seizure types was reported, although focal seizures were the most common. Encephalopathy related to status epilepticus during slow-wave sleep (ESES)/developmental epileptic encephalopathy with spike-wave activation during sleep (DEE-SWAS) was diagnosed in >25% of the individuals. All but one individual presented with neurodevelopmental delay. Regression in verbal and/or motor domains was observed in all individuals who suffered from ESES/DEE-SWAS, as well as some who did not. We could not identify a clear genotype-phenotype relationship even between individuals with the same DLG4 variants. SIGNIFICANCE: Our study shows that a subgroup of individuals with DLG4-related synaptopathy have DEE, and approximately one fourth of them have ESES/DEE-SWAS. Our study confirms DEE as part of the DLG4-related phenotypic spectrum. Occurrence of ESES/DEE-SWAS in DLG4-related synaptopathy requires proper investigation with sleep EEG.

Developing a phenotype risk score for tic disorders in a large, clinical biobank.

Tics are a common feature of early-onset neurodevelopmental disorders, characterized by involuntary and repetitive movements or sounds. Despite affecting up to 2% of children and having a genetic contribution, the underlying causes remain poorly understood. In this study, we leverage dense phenotype information to identify features (i.e., symptoms and comorbid diagnoses) of tic disorders within the context of a clinical biobank. Using de-identified electronic health records (EHRs), we identified individuals with tic disorder diagnosis codes. We performed a phenome-wide association study (PheWAS) to identify the EHR features enriched in tic cases versus controls (n = 1406 and 7030; respectively) and found highly comorbid neuropsychiatric phenotypes, including: obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorder, and anxiety (p < 7.396 × 10-5). These features (among others) were then used to generate a phenotype risk score (PheRS) for tic disorder, which was applied across an independent set of 90,051 individuals. A gold standard set of tic disorder cases identified by an EHR algorithm and confirmed by clinician chart review was then used to validate the tic disorder PheRS; the tic disorder PheRS was significantly higher among clinician-validated tic cases versus non-cases (p = 4.787 × 10-151; ß = 1.68; SE = 0.06). Our findings provide support for the use of large-scale medical databases to better understand phenotypically complex and underdiagnosed conditions, such as tic disorders.