The Hidden Genome of Treatment: Lessons for Epilepsy Pharmacogenomics from GLP-1 Agonists

Signal. I admit that the title of this blog post is somewhat misleading, but please bear with me. Yes, GLP-1 receptor agonists have very little to do with epilepsy, but there is a larger story behind this. In a recent study, nearly 28,000 people taking GLP-1 receptor agonists answered a seemingly simple question: how much weight did you lose, and how bad were the side effects? This simple survey, coupled with genetic data, produced one of the cleanest pharmacogenomic signals seen in recent years. But it also emphasized that the genetics of treatment are often not the genetics of disease, and that matters far beyond obesity and weight loss. Here is why this should make us rethink pharmacogenomics in epilepsy.

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STRIPE – When RNA Speaks Louder Than DNA

RNA. More than a decade ago, I remember reading an article arguing that we actually live in an RNA world. At the time, this felt a bit academic and not really relevant. Genetics was about sequencing and interpreting DNA. However, over the last few years, our ability to think in terms of RNA transcripts rather than DNA sequence has become increasingly relevant. When I teach trainees, I sometimes tell them: we do not care about genes. And then I pause, usually long enough to make people uncomfortable. Then I correct myself: we care about transcripts. In a recent publication, we assessed how a novel targeted long-read RNA sequencing approach can help with rare disease diagnosis. Here is what we found.

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Signals in the noise – qEEG patterns in genetic epilepsies

qEEG. The electroencephalogram is one of the oldest tools in neurology. We use it every day to diagnose and monitor brain function, yet, even in the era of genomic medicine, most of our EEG interpretation still relies on visual inspection, a human reading of squiggled traces. In a recent publication in Neurology, we asked whether the information embedded in these signals could be measured more objectively in children with STXBP1, SCN1A, and SYNGAP1-related disorders. Here is the story on how we identified hidden signals in the EEG tracings of individuals with genetic epilepsies.

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The quiet revolution – revising ACMG criteria for epilepsy genes

VUS. The story begins with a patient in clinic. A young child with severe epilepsy, carrying a variant in SCN1A, the classic gene for Dravet Syndrome. But the variant is labeled a variant of uncertain significance (VUS). Dravet Syndrome is a clinical diagnosis, and the treatments we have today do not hinge on whether the variant is clearly pathogenic or not. But then we wonder whether a novel precision therapy could be an option, and we look up inclusion criteria and hesitate. Trial frameworks often require a variant to be pathogenic or likely pathogenic, and future precision medicine approaches in routine clinical care may require the same. For this patient, a VUS is a door that does not open. Here lies the quiet revolution in epilepsy genetics that is unfolding in the background: the refinement of variant interpretation itself.

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The power of paralogs in epilepsy genetics

Paralogs. Every week in our variant review meetings, we encounter a familiar issue: understanding a missense variant of uncertain significance. Unless it matches a known disease-associated variant or is found to be de novo, our confidence often stalls. But what happens if we stopped looking at genes in isolation? In a recent publication, we had the opportunity to explore this idea by looking at paralogs and variants at identical sites across gene families, and we found evidence that was strong enough to be included in the official ACMG/AMP variant curation criteria. Continue reading

RBFOX3 and the hunt for epilepsy genes in 100,000 genomes

Large scale. Novel epilepsy genes are typically discovered through collaborative studies that combine information across various centers and research groups. However, there are also large-scale sequencing initiatives on a national level that include individuals with epilepsy. In a recent study published in Nature, a wide range of clinical phenotypes were assessed in an initial cohort of 34,000 individuals in the UK 100,000 Genomes Project. Let me dive into the associations related to epilepsy in this publication.

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Predicting genetic epilepsies through EMR fingerprints

EMR. Clinical data on rare disease is not necessarily rare; it is our ability to unlock already existing data that is rare. Over the last decade, we have tried to understand the fingerprints that rare genetic epilepsies leave in the electronic medical record (EMR). In our flagship publication last year, we tried to push the boundary. Is EMR data, with all its strength and weaknesses, able to predict genetic diagnosis? Here is our journey through the hidden signals in large EMR datasets.

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SCN1A gain-of-function, paralogs, and the Philadelphia variant

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.

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The new genetics of Dravet Syndrome

Sundance. I was asked to give a talk on the genetics of Dravet Syndrome at the Dravet Syndrome Foundation meeting in Fort Worth, Texas. I started my presentation asking the question whether there is actually anything novel to talk about given that it is well established that Dravet Syndrome is due to loss-of-function variants in SCN1A, and the challenges are in finding better treatments, not in refining SCN1A genetics. However, this is not quite true. There are several new aspects regarding the genetics of Dravet Syndrome that are worth highlighting. Continue reading

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