The advent of next generation DNA sequencing has revolutionized gene discovery in human diseases, including epilepsy. Hundreds of genes have been implicated in epilepsy in the last decade, revealing the diversity of biological mechanisms that can go awry in this disorder. However, the rate at which we are identifying new genes involved in epilepsy is now outpacing our ability to study disease mechanisms. Moreover, clinical gene panel or exome sequencing has become standard practice for patients with early-onset, familial, and refractory epilepsies. This rapid assimilation of genetic testing into clinical care has led to a surge in the number of genetic variants of uncertain significance (VUS), particularly the occurrence of missense VUS. These VUS are assigned to an indeterminate spectrum between pathogenic and benign, which complicate interpretation for genetic counselors, clinicians, patients and families, as well as assessment of the need for further testing. Here we propose a Center without Walls, entitled Epilepsy Multiplatform Variant Prediction (EpiMVP), spanning 5 institutions and incorporating expertise from geneticists, clinicians, computational biologists, neuroscientists, stem cell biologists, pharmacologists and electrophysiologists who have a proven track record of collaborative publications and grants, as well as stature as leaders of national and international epilepsy organizations. EpiMVP will develop a modular, highly integrated platform approach to accelerate determination of the functional, pharmacological, neuronal network and whole animal consequences of genetic variants implicated in a range of clinical epilepsy types. We will study non-ion-channel, non-receptor genes commonly implicated in epilepsy, and that are involved in diverse biological processes. Our ultimate goals are to devise an effective experimental platform for testing the pathogenicity of VUS in genes implicated in epilepsy and to generate a computational model (EpiPred) that predicts the likelihood that a variant is pathogenic or benign. This work is crucial in the pursuit of novel therapeutics and the promise of personalized medicine. The overall milestones of the Center are: 1. Evaluate genes associated with epilepsy and select candidates for analysis, model data for, and analyze all project data for development of EpiPred an iterative machine learning model to classify variants in genes implicated in epilepsy. 2. Test selected VUS using medium throughput, in vitro approaches. 3. Test selected VUS in human cortical neurons or human brain organoids using induced pluripotent stem cell approaches. 4. Test selected VUS in pre-clinical, in vivo models. The expected outcomes are: 1. Provide a freely available prediction tool for clinicians to differentiate between pathogenic and benign variants for genes implicated in epilepsy; 2. Provide experimental models to study the functional consequences of specific variants; 3. Provide a reclassification of VUS in ClinVar/ClinGen and to develop new guidelines for incorporating functional readouts into the ACMG criteria; 4. Inform the future development of novel therapeutics to treat epilepsy.
Here, we propose a Center without Walls, entitled Epilepsy Multiplatform Variant Prediction (EpiMVP), spanning five institutions and incorporating expertise from geneticists, clinicians, computational biologists, neuroscientists, stem cell biologists, pharmacologists and electrophysiologists who have a proven track record of collaborative publications and grants, as well as stature as leaders of national and international epilepsy organizations. EpiMVP will develop a modular, highly integrated platform approach to accelerate determination of the functional, pharmacological, neuronal network and whole animal consequences of genetic variants among a range of clinical epilepsy types. Our ultimate goal is to devise an effective platform for testing the pathogenicity of variants of uncertain significance in non-ion channel, non-receptor genes implicated in epilepsy and for identifying potential targets for future intervention.
