EMR. Genomic data is increasingly available for large patient cohorts. In parallel, healthcare is increasingly digitized and large amounts of data can easily be extracted and analyzed at the click of a button. In principle, this should provide tremendous opportunities to understand how epilepsy care can be personalized based on genetic factors. However, we quickly run into challenges. Obtaining information on seizure frequencies, for example, requires manual chart review. Trying to understand how a person’s genetic makeup affects responses to anti-seizure medications is therefore not possible in large healthcare systems where related questions in other diseases can increasingly be answered. Here is a brief overview of how we can meaningfully engage with clinical data when outcomes are simply not available. Continue reading
Isolates. Last week, the FinnGen biobank went live, and Nature dedicated an entire issue to the launch of this initiative. In brief, FinnGen is a large Finnish research project providing genomic and clinical data from a Finnish biobank with the aim to provide new insights into human disease. Finland is an isolated population, which offers unique insights into the role of rare variants in disease. When I checked the FinnGen database for association with SCN1A, I was surprised that three missense variants have been associated with various diseases. Here is what a founder population can tell us about the various roles of SCN1A in human disease. Continue reading
A long-awaited answer. Gene discovery in the epilepsies is continuing, and some novel genetic etiologies are quite surprising given that the particular genes had previously been described in a completely different context. One of these examples is TRPM3. In our recent publication, we further define TRPM3 as a gene causative of a variety of neurodevelopmental disorders. Also notably, we find that the anti-seizure medication primidone can be a helpful treatment in individuals with TRPM3. Beyond outlining the TRPM3 spectrum, our publication helped us find a long-awaited diagnosis for one of our research participants, one that took four years to prove. Here is the TRPM3 story. Continue reading
Timeline. There are a few factors converging at the moment that motivated me to write this blog post. Our blog is officially 14 years old, a fact that has generated surprise, but also nostalgia over the weekend. Second, we were asked to provide an editorial for an interesting review paper by the Lal group, which data-mined PubMed to characterize the history of epilepsy gene discovery. And third, I have heard too often that our 2016 timeline of epilepsy gene discovery that is often used in presentations is antiquated. Let us provide everybody with an update in this blog post. But first, let’s start with a seemingly easy question: what exactly is an epilepsy gene? Continue reading
Between the ion channels. Rather than going “beyond the ion channel,” in this post, we aim to look between them. We want to dive into a study where examining the group of epilepsy-related sodium channels was initially more informative than the single gene itself—even when that gene was SCN1A, the most established epilepsy gene. A recurrent SCN1A variant turned out to be part of an emerging, previously underappreciated gain-of-function spectrum. Here, we discuss the unusual phenotype of SCN1A gain-of-function variants and how we are currently working on integrating information on paralogs into the official ACMG variant curation criteria.
800 years. The discovery of SCN1B as a causative gene for Genetic Epilepsy with Febrile Seizures Plus (GEFS+) was one of the most pivotal moments in epilepsy genetics. This discovery not only shaped our understanding of the channelopathy concept, but also highlighted the importance of careful phenotyping. Therefore, it may be surprising that SCN1B took almost a quarter of a century to accrue sufficient evidence to be considered as a definite epilepsy gene. However, this is not the only aspect where SCN1B operates on its own time scale. In a recent publication, one of the most common disease variants in SCN1B could be traced back more than 800 years to a single founder event. Here is a 2023 update on the journey of one of the most well-known but also most mysterious epilepsy genes whose origins are lost in the depth of time. Continue reading
Postsynaptic. SYNGAP1-related disorders are among the most common genetic developmental and epileptic encephalopathies with a unique clinical presentation. However, since the initial gene discovery in 2009, the clinical spectrum has expanded significantly to include a wider range of epilepsies and seizure types. Additionally, the SYNGAP1 community has grown to encompass hundreds of individuals reported in the literature or organized in advocacy organizations. Accordingly, we wanted to use the opportunity to update our SYNGAP1 page. Here are three things to know about SYNGAP1 in 2023.
Data sharing. Over time, genomic scientists have learned how to share. Large international cohorts and efforts of data deposition have led to large databases that can be used to answer big questions. However, silos of genomic data, such as massive sequencing studies performed on specialized cohorts, lay unconnected across research groups, academic institutions, and collaborators. Recently, we have been involved in several projects to de-silo rather than simply share genomic data, and we realized that there may be some aspects that apply to the genomics worlds more broadly. For example, what makes de-siloing different from data sharing? The goal of this post is to redefine these concepts and explain why we should be less concerned about data sharing and more concerned about data integration. Continue reading