The SCN1A rs6732655 enigma – a reply

rs6732655. I acknowledge that the title of this blog post looks like my keyboard is broken, but please bear with me. Last month, I blogged about a recent genome-wide association by the BioBank Japan (BBJ), discussing the evidence for a Single Nucleotide Polymorphism (SNP) in the vicinity of the SCN1A gene (rs6732655). In a prior study, the SNP in question was initially found to be associated with epilepsy and I discussed the fact that this SNP, albeit not significant by itself, was also seen at a higher frequency in cases than in controls in the epilepsy cohort of the BBJ study. I received some comments regarding this post and it was pointed out that my reasoning was incorrect given that rs6732655 was not nominally significant in the BBJ study. Therefore, this study was not a replication study in itself. Let me retrace my steps and revisit where my hunch came from to write the initial blog post. Continue reading

Entering the phenotype era – HPO-based similarity, big data, and the genetic epilepsies

Semantic similarity. The phenotype era in the epilepsies has now officially started. While it is possible for us to generate and analyze genetic data in the epilepsies at scale, phenotyping typically remains a manual, non-scalable task. This contrast has resulted in a significant imbalance where it is often easier to obtain genomic data than clinical data. However, it is often not the lack of clinical data that causes this problem, but our ability to handle it. Clinical data is often unstructured, incomplete and multi-dimensional, resulting in difficulties when trying to meaningfully analyze this information. Today, our publication on analyzing more than 31,000 phenotypic terms in 846 patient-parent trios with developmental and epileptic encephalopathies (DEE) appeared online. We developed a range of new concepts and techniques to analyze phenotypic information at scale, identified previously unknown patterns, and were bold enough to challenge the prevailing paradigms on how statistical evidence for disease causation is generated. Continue reading

The natural history of genetic epilepsies as told by 3,200 years of electronic medical records

EMR. When we consider the natural history of rare diseases like the genetic epilepsies, we typically think about a lack of longitudinal data that contrasts with the abundant genetic information that is available nowadays – the so-called phenotyping gap. We typically suggest that we need to obtain this information in future prospective studies to better understand long-term outcome, response to medications, and potential early warning signs for an adverse disease course. However, a vast amount of clinical data is collected on an ongoing basis through electronic medical records (EMR) as a byproduct of regular patient care. In a recent study, our group built tools to mine the electronic medical records to assess the disease history of 658 individuals with known or presumed epilepsies using clinical information collected at more than 62,000 patients encounters across more than 3,200 patient years. Here is a brief summary of our first study on EMR genomics, an untapped resource that has the potential to improve our understanding of the genetic epilepsies. Continue reading

GNAO1 and 13K genomes – rare disease sequencing on a national level

WGS. Whole-genome sequencing is increasingly used to understand the cause of rare diseases in a research and diagnostic context. However, while the usefulness of this technology has been shown in smaller studies, it remains unclear whether strategies to understand the cause of rare disorders through whole genome sequencing can be performed on a national level. A recent study in Nature reported the first results from a national sequencing campaign for rare disorders in the UK, including the analysis of more than 13,000 genomes. In this blog post, I would like to focus on the neurogenetics component of this enormous study, which identified disease-causing variants in GNAO1 as the most common cause within the study’s subgroup of neurological and developmental disorders. Continue reading

Common genetic risk factors for epilepsy in the Japanese population

GWAS. While our blog mainly deals with monogenic epilepsies, assessing common genetic risk factors through genome-wide association studies has been an established way of understanding potential genetic contributors to both common and rare disorders. More recently, polygenic risk scores have entered the stage, composite measures of many common variants which explain a significant proportion of the overall population risk for epilepsy. However, a major limitation of many genome-wide association studies has been the focus on populations of European ancestry. So far, very few studies have examined common genetic risk factors in the epilepsies in non-European populations. In a recent publication examining results from the BioBank Japan Project, 42 disorders were examined in more than 200,000 individuals, including the epilepsies. While no single epilepsy variant stood out, the study provides an interesting confirmation of a previously known common risk factors for the epilepsies. Continue reading

SCN1A-related epileptic encephalopathy: Beyond Dravet syndrome

SCN1A phenotypes. Readers of Beyond the Ion Channel will know that we often post about SCN1A, one of the first discovered and most common genetic causes of epileptic encephalopathy. We more or less assume that we understand the phenotypes associated with pathogenic variants in SCN1A: most commonly Dravet syndrome, which is associated with de novo variants, and less commonly genetic epilepsy with febrile seizures plus (GEFS+), associated with inherited missense variants. However, a recent publication by Sadleir and colleagues suggests that the phenotypic spectrum of SCN1A-related disorders may be broader than we have previously appreciated. Are there SCN1A-related epileptic encephalopathies in addition to Dravet syndrome? Continue reading

SCN1A – what’s new in 2016?

The story of SCN1A. Variants in SCN1A were first reported in association with epilepsy in 2000, when familial heterozygous SCN1A missense variants were identified in two large families with GEFS+. The phenotype was characterized by incomplete penetrance and significant variable expressivity between family members, making it clear from the beginning that the SCN1A story would not be simple. Within the next few years, we learned that SCN1A variants could cause a wide spectrum of epilepsy phenotypes, including GEFS+, Dravet syndrome, intractable childhood epilepsy with generalized tonic-clonic seizures, and, less frequently, infantile spasms and simple febrile seizures. As it became clear that SCN1A variants played an important role in genetic epilepsies, focus turned towards understanding the mechanism underlying seizure genesis, as well as identifying management and therapy options. Even after 15 years of study, our understanding of SCN1A-related epilepsy is still evolving. Keep reading to learn more about the most recent discoveries related to SCN1A. Continue reading

The story of the missed SCN1A mutations

Dravet Syndrome. In 2011, our EuroEPINOMICS-RES program was in full swing. We had recruited a cohort of 31 patients with Dravet Syndrome who had been previously tested negative for mutations in SCN1A with the aim to identify novel genes for this epileptic encephalopathy. Even though this cohort was crucial in our identification of CHD2, HCN1, and KCNA2 as novel genes for genetic epilepsies, the main finding in this cohort was something that we did not expect. Roughly one third of our 31 patients had mutations in SCN1A, even though they had previously been tested negative. In a recent publication in Molecular Genetics and Genomic Medicine, we tried to understand what had happened and joined forces with other groups who had made the same observation. Here is the story of the missed SCN1A mutations. Continue reading

The three twists in the SCN1A story that you didn’t know about

SCN1A. Finally, after various other epilepsy genes have been added, we are trying to put together a static website on SCN1A rather than updates only. SCN1A is by far the most prominent epilepsy gene and the first genetic etiology that comes to mind for anything relating to fever and seizures. While our Epilepsiome page will give you all the relevant facts regarding this gene, here is my personal view on the SCN1A story. Continue reading