AI Tool Helps Identify Disease-Causing Epilepsy Variants in STXBP1 Gene
Northwestern Medicine scientists developed EpiPred, a machine learning model that predicts whether genetic variants in the STXBP1 gene cause severe childhood epilepsy, addressing a critical gap where many variants are classified as uncertain significance and prevent patients from accessing gene-targeted therapies. The model outperformed existing prediction tools and identified approximately one-quarter of variants currently classified as uncertain may actually be disease-causing. The team made the tool publicly available and is developing high-throughput methods to evaluate thousands of variants simultaneously, with potential applications extending to other rare genetic disorders.