A VUS in the context of epilepsy is a genetic change whose impact on an individual’s epilepsy risk is not yet known. Everyone’s genetic code is slightly different. Some changes in genes, called variants, do not affect a given gene’s function and therefore do not increase epilepsy risk. Other genetic changes prevent proper functioning of the protein encoded by the gene and confer an increased risk of epilepsy.

Gene variants can be categorized into different groups, including known/probably pathogenic (disease-causing) versus known/probably benign. These designations are based largely upon databases of gene sequences for control populations (without epilepsy), combined with predictive algorithms that determine the probability that the genetic variant would adversely impact protein function. Often, however, not enough information is available to determine if a variant is normal or pathogenic, and these variants are classified as VUS. This multi-institutional collaborative grant is focused on improving our ability to determine whether variants in specific epilepsy genes are pathogenic or benign. The goal is to develop a predictive tool that can be used by clinicians to better categorize gene variants identified in their epilepsy patients and thus improve treatment plans and patient outcomes. The tool will also be useful for scientists studying these epilepsy genes.

EpiMVP brings together neuroscientists, physiologists, pharmacologists, stem cell biologists, bioinformaticians, clinicians, geneticists and industry partners, all with expertise in studying, diagnosing or treating genetic epilepsies. This unique collaboration involves the University of Michigan, Weill-Cornell Medicine, Northwestern University, the University of California, San Francisco, and St. Jude Children’s Research Hospital. The experimental approaches involve the use of cell culture models, including human pluripotent stem cells and brain organoids, whole-animal models using rodents and zebrafish, genome editing techniques and machine learning algorithms to test whether epilepsy gene variants are benign or disease-causing in these model systems, and develop a tool to accurately predict gene variant effects in people with genetic epilepsies.