This month we feature several new discoveries and technological advances in epilepsy research. First, we share news of a study that identified more than 900 proteins tied to epilepsy, including a particular protein called G Protein Subunit 1, which the researchers found to be most significantly changed across all brain regions examined in the study.

Two other studies examine the role of genetics in epilepsy. In the first study, researchers linked clinical information such as autism and epilepsy to genetic abnormalities in individuals with SCN2A-related disorder. In the second study, researchers explored the role of mutations in the neurochondrin gene in children with different degrees of neurodevelopmental delay and epilepsy.

Finally, we highlight two studies that utilize advanced technology. The first study uses a mathematical model to predict seizures, and the second uses deep learning to improve the interpretation of brain activity in individuals with epilepsy.

• Identifying Epilepsy Drug Targets: An analysis of human brain tissue revealed more than 900 proteins tied to epilepsy, which researchers identify as potential new targets for epilepsy treatments. One protein stood out as the most significantly reduced across all brain regions studied. Called G Protein Subunit 1, or GNB1, the protein is known to play an important role in communication throughout the brain, although the researchers say its precise role in epilepsy remains unclear. Learn more.
   
• Epilepsy and Autism: Researchers compiled a complete genetic and clinical analysis of more than 400 individuals with SCN2A-related disorder, which has been linked to a variety of neurodevelopmental disorders including epilepsy and autism. In the study, the researchers used an analytical method called Human Phenotype Ontology, which standardized a patient's clinical features and allowed this clinical data to be translated similar to genetic data. This method allowed the researcher to link clinical features such as epilepsy and autism with genetic abnormalities. By linking clinical features to genetic abnormalities in a standardized format, the researchers hope their findings lead to improved identification of neurodevelopmental disorders and clinical interventions. Learn more.
   
• Epilepsy Genetics: Mutations in the neurochondrin (NCDN) gene can cause epilepsy, neurodevelopmental delay and intellectual disability, according to a recent study. The researchers also found that the NCDN gene mutation significantly impairs signaling between neurons in the brain and conclude that this finding highlights a critical role for the NCDN gene in human brain development. Learn more.
   
• Seizure Prediction: A research team has created a seizure-predicting mathematical model that is designed to give people with epilepsy a warning five minutes to one hour before they are likely to experience a seizure. An electrical implant on the person's brain collects brain signal data to find patterns of brain activity that indicate when a person is at risk of having a seizure. Learn more.
   
• Deep Learning to Interpret EEG: Deep learning models can help neurologists interpret epileptic brain activity during and between seizures from relatively few scalp electroencephalography (EEG) readings. Deep learning in combination with human EEG review can lower the time of manual EEG review while maintaining the benefits of having an expert human EEG reviewer. Learn more.