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.

Endocannabinoid dysfunction in neurological disease: neuro-ocular DAGLA-related syndrome.

The endocannabinoid system is a highly conserved and ubiquitous signalling pathway with broad-ranging effects. Despite critical pathway functions, gene variants have not previously been conclusively linked to human disease. We identified nine children from eight families with heterozygous, de novo truncating variants in the last exon of DAGLA with a neuro-ocular phenotype characterized by developmental delay, ataxia and complex oculomotor abnormality. All children displayed paroxysms of nystagmus or eye deviation accompanied by compensatory head posture and worsened incoordination most frequently after waking. RNA sequencing showed clear expression of the truncated transcript and no differences were found between mutant and wild-type DAGLA activity. Immunofluorescence staining of patient-derived fibroblasts and HEK cells expressing the mutant protein showed distinct perinuclear aggregation not detected in control samples. This report establishes truncating variants in the last DAGLA exon as the cause of a unique paediatric syndrome. Because enzymatic activity was preserved, the observed mislocalization of the truncated protein may account for the observed phenotype. Potential mechanisms include DAGLA haploinsufficiency at the plasma membrane or dominant negative effect. To our knowledge, this is the first report directly linking an endocannabinoid system component with human genetic disease and sets the stage for potential future therapeutic avenues.

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.

Developing a Phenotype Risk Score for Tic Disorders in a Large, Clinical Biobank.

Importance: Tics are a common feature of early-onset neurodevelopmental disorders, characterized by involuntary and repetitive movements or sounds. Despite affecting up to 2% of young children and having a genetic contribution, the underlying causes remain poorly understood, likely due to the complex phenotypic and genetic heterogeneity among affected individuals. Objective: In this study, we leverage dense phenotype information from electronic health records to identify the disease features associated with tic disorders within the context of a clinical biobank. These disease features are then used to generate a phenotype risk score for tic disorder. Design: Using de-identified electronic health records from a tertiary care center, we extracted individuals with tic disorder diagnosis codes. We performed a phenome-wide association study to identify the features enriched in tic cases versus controls (N=1,406 and 7,030; respectively). These disease features were then used to generate a phenotype risk score for tic disorder, which was applied across an independent set of 90,051 individuals. A previously curated set of tic disorder cases from an electronic health record algorithm followed by clinician chart review was used to validate the tic disorder phenotype risk score. Main Outcomes and Measures: Phenotypic patterns associated with a tic disorder diagnosis in the electronic health record. Results: Our tic disorder phenome-wide association study revealed 69 significantly associated phenotypes, predominantly neuropsychiatric conditions, including obsessive compulsive disorder, attention-deficit hyperactivity disorder, autism, and anxiety. The phenotype risk score constructed from these 69 phenotypes in an independent population was significantly higher among clinician-validated tic cases versus non-cases. Conclusions and Relevance: Our findings provide support for the use of large-scale medical databases to better understand phenotypically complex diseases, such as tic disorders. The tic disorder phenotype risk score provides a quantitative measure of disease risk that can be leveraged for the assignment of individuals in case-control studies or for additional downstream analyses.