October 3, 2024
by Ari Navetta, Broad Institute of MIT and Harvard
Epilepsy genetic architecture from large-scale genetic association studies. Credit: Nature Neuroscience (2024). DOI: 10.1038/s41593-024-01747-8
The largest and most diverse study to date of epilepsy’s genetic factors has revealed new potential targets for treatment, both shared by and unique to different subtypes of epilepsy. The findings point to factors involved in how neurons communicate and fire, suggesting potential targets for new therapies. In the future, the results could also help doctors tailor treatments to a patient’s genome.
Epilepsy is one of the most common neurological disorders. Scientists have long known that genetics play a major role in epilepsy risk, but identifying all of the specific genetic contributions has been challenging, and previous studies have focused on just one or a few genes at a time. Epilepsy also has several subtypes, and while one group called developmental encephalopathies has been connected to several genes, other forms of the disease are less well understood.
The study, published in Nature Neuroscience, comes from the Epi25 Collaborative, a group of over 200 researchers around the world working to uncover the genetic basis of epilepsy. It builds on previous work by the group using ever-larger cohorts of participants, now up to more than 54,000 people—nearly double previous studies.
The researchers—led by Benjamin Neale, co-director of the Stanley Center for Psychiatric Research at the Broad Institute of MIT and Harvard and a core faculty member of the Analytic and Translational Genetics Unit at Massachusetts General Hospital; and Samuel Berkovic, a professor of medicine at the University of Melbourne—used an approach called whole exome sequencing to look at every gene in the protein-coding region of the genome.
“For a complex and heterogeneous disorder like epilepsy, we really wanted to survey as comprehensive a sample as possible across a wide range of genetic variation,” said first author Siwei Chen, a postdoctoral scholar in Neale’s lab.
Results from gene-based burden analysis of URVs. a,b, Burden of protein-truncating (a) and damaging missense (b) URVs in each protein-coding gene with at least one epilepsy or control carrier. The observed −log10-transformed P values are plotted against the expectation given a uniform distribution. For each variant class, burden analyses were performed across four epilepsy groups—1,938 DEEs, 5,499 GGE, 9,219 NAFE and 20,979 epilepsy-affected individuals combined—versus 33,444 controls. P values were computed using a Firth logistic regression model testing the association between the case–control status and the number of URVs (two-sided); the red dashed line indicates exome-wide significance, P = 3.4 × 10−7, after Bonferroni correction (Methods). The top 10 genes with URV burden in epilepsy are labeled. Credit: Nature Neuroscience (2024). DOI: 10.1038/s41593-024-01747-8
Ultra-rare variants
Since 2014, Epi25 has collected information from patients with multiple types of epilepsy, including a severe group of epilepsies known as developmental and epileptic encephalopathies, as well as more common and milder forms called genetic generalized epilepsy and non-acquired focal epilepsy (NAFE).
To find genes that strongly contribute to these subtypes, the authors searched the participants’ exomes for “ultra-rare” variants, or URVs—mutations found less than once per 10,000 participants. If these variants are found more often in people with epilepsy than in those without, or in one type of epilepsy than another, they are more likely to play a role in the disease.
Since URVs are so rare, and because the scientists wanted to understand many different types of epilepsy, the researchers analyzed DNA from people across the world with a range of different genetic ancestries to find meaningful signals. The study’s 54,000 participants included about 21,000 patients with epilepsy and 33,000 controls.
The exomes revealed connections between disease risk and several genes involved in the transmission of signals across the synapses between neurons. In particular, genes coding for ion channel protein complexes, such as receptors for the neurotransmitter GABAA, play a major role in epilepsy risk across subtypes. While this trend was present for all subtypes, the specific variants contributing to mutations in ion channel proteins varied when looking at each subtype individually.
To improve their ability to focus on specific cellular pathways, the researchers aggregated data from genes with similar functions or that encode parts of the same protein complex. For example, data from patients with NAFE showed a strong signal for the gene DEPDC5, which encodes a part of a protein complex called GATOR1 that is critical to brain cell function. When combining it in their analysis with the two genes that encode the rest of the GATOR1 complex, the signal became even stronger, indicating that GATOR1 may be highly involved in a mechanism that contributes to NAFE.
In the future, the results could help doctors tailor treatment strategies based on a patient’s genotype, or stratify patients based on the biological effects of specific variants. The researchers say the findings could also improve genetic testing for epilepsy and provide a clearer sense of how genetic variation leads to disease.
“These genetic insights provide data-driven starting points for unraveling the biology of epilepsies,” said Neale, “which in turn should help spur future, subtype-tailored advances in diagnosis and treatment.”
Summary-level data from the study is available via the Epi25 WES Browser, an interactive browser hosted by the Broad Institute, allowing clinicians to easily look up variants seen in their patients and facilitating clinical and translational efforts in follow-up studies.
More information: Epi25 Collaborative, Exome sequencing of 20,979 individuals with epilepsy reveals shared and distinct ultra-rare genetic risk across disorder subtypes, Nature Neuroscience (2024). DOI: 10.1038/s41593-024-01747-8
Journal information: Nature Neuroscience
Provided by Broad Institute of MIT and Harvard
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