Synaptic. Identifying the genetic changes underlying severe childhood epilepsies is one of the key steps for predicting outcomes and developing better treatments. However, while our ability to analyze genetic data at scale allows us to simultaneously query tens of thousands of exomes or genomes, our understanding of large phenotypic data has been limited. This limitation, the “phenotypic bottleneck”, is often frustrating, especially as many developmental and epileptic encephalopathies present with unusual and very complex phenotypic features that we would like to better understand for our clinical decision making. The lack of concepts and methods to handle large amounts of phenotypic data has been one of the main contributing factors to this shortcoming. In a new publication in the American Journal of Human Genetics, we aim to overcome this problem by identifying a measurement for phenotypic similarity, using a computational approach to determine how similar patients are to each other based on Human Phenotype Ontology terms. When combined with exome sequencing data, we identified AP2M1, a gene that caused such a similar phenotype that it stood out from the remainder of the cohort. It is the first epilepsy-associated gene identified not from a genetic association, but from phenotypic similarity. Continue reading