Pitfalls in genetic testing: the story of missed SCN1A mutations

BACKGROUND: Sanger sequencing, still the standard technique for genetic testing in most diagnostic laboratories and until recently widely used in research, is gradually being complemented by next-generation sequencing (NGS). No single mutation detection technique is however perfect in identifying all mutations. Therefore, we wondered to what extent inconsistencies between Sanger sequencing and NGS affect the molecular diagnosis of patients. Since mutations in SCN1A, the major gene implicated in epilepsy, are found in the majority of Dravet syndrome (DS) patients, we focused on missed SCN1A mutations. METHODS: We sent out a survey to 16 genetic centers performing SCN1A testing. RESULTS: We collected data on 28 mutations initially missed using Sanger sequencing. All patients were falsely reported as SCN1A mutation-negative, both due to technical limitations and human errors. CONCLUSION: We illustrate the pitfalls of Sanger sequencing and most importantly provide evidence that SCN1A mutations are an even more frequent cause of DS than already anticipated

Diagnostic implications of genetic copy number variation in epilepsy plus

OBJECTIVE: Copy number variations (CNVs) represent a significant genetic risk for several neurodevelopmental disorders including epilepsy. As knowledge increases, reanalysis of existing data is essential. Reliable estimates of the contribution of CNVs to epilepsies from sizeable populations are not available. // METHODS: We assembled a cohort of 1255 patients with preexisting array comparative genomic hybridization or single nucleotide polymorphism array based CNV data. All patients had "epilepsy plus," defined as epilepsy with comorbid features, including intellectual disability, psychiatric symptoms, and other neurological and nonneurological features. CNV classification was conducted using a systematic filtering workflow adapted to epilepsy. // RESULTS: Of 1097 patients remaining after genetic data quality control, 120 individuals (10.9%) carried at least one autosomal CNV classified as pathogenic; 19 individuals (1.7%) carried at least one autosomal CNV classified as possibly pathogenic. Eleven patients (1%) carried more than one (possibly) pathogenic CNV. We identified CNVs covering recently reported (HNRNPU) or emerging (RORB) epilepsy genes, and further delineated the phenotype associated with mutations of these genes. Additional novel epilepsy candidate genes emerge from our study. Comparing phenotypic features of pathogenic CNV carriers to those of noncarriers of pathogenic CNVs, we show that patients with nonneurological comorbidities, especially dysmorphism, were more likely to carry pathogenic CNVs (odds ratio = 4.09, confidence interval = 2.51-6.68; P = 2.34 × 10-9 ). Meta-analysis including data from published control groups showed that the presence or absence of epilepsy did not affect the detected frequency of CNVs. // SIGNIFICANCE: The use of a specifically adapted workflow enabled identification of pathogenic autosomal CNVs in 10.9% of patients with epilepsy plus, which rose to 12.7% when we also considered possibly pathogenic CNVs. Our data indicate that epilepsy with comorbid features should be considered an indication for patients to be selected for a diagnostic algorithm including CNV detection. Collaborative large-scale CNV reanalysis leads to novel declaration of pathogenicity in unexplained cases and can promote discovery of promising candidate epilepsy genes

Pitfalls in genetic testing: the story of missed SCN1A mutations

Peer reviewe

V28. KCNA2 mutations cause epileptic encephalopathy by gain- or loss-of channel function

Epileptic encephalopathies (EE) are a heterogeneous group of epilepsy syndromes associated with severe cognitive and behavioral disturbances. Amongst others, genes encoding neuronal ion channels have been identified as candidate genes for EE. Using next generation sequencing, we identified four different de novo mutations in KCNA2, encoding the voltage-gated potassium channel KV1.2. Voltage-gated potassium channels play an essential role in neuronal excitability, control the resting membrane potential and thresholds for action potential generation of a neuron and are responsible for repolarizing membranes back to resting values after action potential generation. Therefore, mutations in potassium channel-encoding genes have been shown to alter the neuronal excitability and cause different epilepsy syndromes, including EE. Here, we identified four independently occurring de novo KCNA2 mutations in six EE patients, with one mutation recurring three times. Four of the studied patients presented with febrile and multiple afebrile, often focal seizure types, multifocal epileptiform discharges strongly activated by sleep, mild-moderate ID, delayed speech development and sometimes ataxia. Functional studies were performed using an automated two-microelectrode voltage-clamp oocyte system. The two mutations associated with this phenotype revealed an almost complete loss-of-function with a dominant negative effect. Two further cases with KCNA2 mutations in the voltage sensor presented with an even more severe EE phenotype. These mutations caused a dramatic gain-of-function effect leading to permanent opening of KV1.2 channels. Therefore, KCNA2 is a novel gene involved in human neurodevelopmental disorders causing the clinical phenotype by two different mechanisms: (i) increasing the excitability or (ii) electrical silencing of KV1.2-expressing neurons

Diagnostic implications of genetic copy number variation in epilepsy plus

Objective: Copy number variations (CNVs) represent a significant genetic risk for several neurodevelopmental disorders including epilepsy. As knowledge increases, reanalysis of existing data is essential. Reliable estimates of the contribution of CNVs to epilepsies from sizeable populations are not available. Methods: We assembled a cohort of 1255 patients with preexisting array comparative genomic hybridization or single nucleotide polymorphism array based CNV data. All patients had \u201cepilepsy plus,\u201d defined as epilepsy with comorbid features, including intellectual disability, psychiatric symptoms, and other neurological and nonneurological features. CNV classification was conducted using a systematic filtering workflow adapted to epilepsy. Results: Of 1097 patients remaining after genetic data quality control, 120 individuals (10.9%) carried at least one autosomal CNV classified as pathogenic; 19 individuals (1.7%) carried at least one autosomal CNV classified as possibly pathogenic. Eleven patients (1%) carried more than one (possibly) pathogenic CNV. We identified CNVs covering recently reported (HNRNPU) or emerging (RORB) epilepsy genes, and further delineated the phenotype associated with mutations of these genes. Additional novel epilepsy candidate genes emerge from our study. Comparing phenotypic features of pathogenic CNV carriers to those of noncarriers of pathogenic CNVs, we show that patients with nonneurological comorbidities, especially dysmorphism, were more likely to carry pathogenic CNVs (odds ratio = 4.09, confidence interval = 2.51-6.68; P = 2.34  7 10 129). Meta-analysis including data from published control groups showed that the presence or absence of epilepsy did not affect the detected frequency of CNVs. Significance: The use of a specifically adapted workflow enabled identification of pathogenic autosomal CNVs in 10.9% of patients with epilepsy plus, which rose to 12.7% when we also considered possibly pathogenic CNVs. Our data indicate that epilepsy with comorbid features should be considered an indication for patients to be selected for a diagnostic algorithm including CNV detection. Collaborative large-scale CNV reanalysis leads to novel declaration of pathogenicity in unexplained cases and can promote discovery of promising candidate epilepsy genes