Five novel concepts in epilepsy genetics you need to know in 2023

Framework. Neurogenetics is evolving, and so is the way we think about the connection between genes and seizures. Over the last few years, several new frameworks of thinking have entered the epilepsy genetics sphere that allow us to think about epilepsy genetics with more nuance. This blog post is dedicated to five known or emerging concepts that are evolving alongside our increased understanding of genetic epilepsies.

Figure 1. Reposting our figure from our publication by McKee and collaborators 2023 demonstrating the value for real world data by predicting next-day seizures in neonates from existing EEG reported collected in our healthcare system [link]. Real world data can be increasingly used to assess outcomes, predict medication responses, or assist in building learning healthcare systems.

1 – Explanatoriness
Let me start with a concept that we previously wrote about. Variant interpretation has become increasingly formal and rule-based, given that it is aimed to be based on a systematic and reproducible framework that spans many disease groups. This leaves a significant number of variants that we consider causative in a clinical context as Variants of Uncertain Significance (VUS) with the formal ACMG framework. Accordingly, we need to think about the additional layer of variant interpretation on top – is a variant explanatory, and not just pathogenic?

2 – Complete and incomplete paralogs
Many genetic etiologies in the epilepsies belong to larger gene families, e.g. voltage-gated sodium channels, potassium channels, or calcium channels. The amino acid sequences are so similar that you can often literally overlay the proteins, and they will share identical amino acids at the corresponding positions. This allows us to “lift over” variants from one gene to the other, comparing “paralogs”. For example, the SCN1A p.R1636Q gain-of-function variant is paralogous to the SCN3A p.R1621Q variant. When amino acid exchanges are identical, there is emerging data that the functional consequences across different genes are similar, i.e. gain-of-function in SCN3A basically predicts a similar gain-of-function effect in SCN1A. When amino acid exchanges are not identical, this situation becomes more complex. Paralogous variants are extremely helpful in interpreting ion channel variants, and we use tools like the PER Viewer more than once a week to better understand variants seen in our clinic.

3 – Real World Data
Every day, literally every minute, individuals with genetic epilepsies generate clinical data that is increasingly captured in electronic format in healthcare systems. While this information was inaccessible only a few years ago, there are increasing attempts to use this information to better understand rare disease. The research area of our group is “EMR Genomics”, trying to outline outcomes and treatment response in genetic epilepsies by combining genomic data with information from the electronic medical records (EMR). Companies such as Ciitizen systematically aggregate this information and provide access to researchers. The value of this information that spans across hundreds of patient years, even for very rare genetic epilepsies, will only increase in the near future and will allow us to get a better sense of outcomes and response to specific medications, in parallel to our pilot work in STXBP1– and SYNGAP1-related disorders.

 4 – Therapeutic microdecisions
This is a concept that is new, but that I have been thinking about quite frequently over the last two years. The idea behind “microdecisions” is that an established genetic diagnosis often changes treatment in frequent, but very small ways. A medication that is started sooner, a sedation for an MRI Brain that is deferred, unusual symptoms that are recognized as either within or outside the spectrum of the genetic diagnosis. None of these decisions alone are game changers, but collectively they improve outcomes. The idea behind “therapeutic microdecisions” is that a genetic diagnosis often does not result in singular, measurable changes such as starting a novel medication that would have been unthinkable otherwise. Alternatively, a genetic diagnosis does more than provide closure for families and psychosocial benefits. A diagnosis of a genetic epilepsy leads to hundreds of microdecisions and collectively, they have the possibility to improve outcomes. This concept stresses the need to systematically track and assess outcomes rather than treatment changes alone when assessing the value of a genetic diagnosis.

5 – Data Desiloing
The fifth concept is the idea of data desiloing that we also introduced in a prior blog post. In brief, we wanted to contrast data sharing (“upon request”) with the active attitude of data desiloing, which includes the active chasing down and harmonization of datasets. Existing datasets have become so complex that a passive approach may often only lead to limited information that can be used. Data desiloing, in contrast, is an activity performed by the recipient of shared data, understanding that data sharing only really works if the receiving party actively uses the data and shapes the process.

What you need to know 
With increasing sophistication, there are new concepts in the field of epilepsy genetics relating to diagnosis and treatment. Explanatoriness of genetic variants, knowledge of complete and incomplete paralogs, the power of Real World Data, the cumulative power of therapeutic microdecisions, and the need for data desiloing are five of the new topics that we think are relevant to capture the changing picture in the field. They capture important new aspects on how we can make sense of genetic variants and data in the epilepsies and neurodevelopmental disorders.

Ingo Helbig is a child neurologist and epilepsy genetics researcher working at the Children’s Hospital of Philadelphia (CHOP), USA.