# Project-005

> **NIH NIH U54** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2020 · $50,418

## Abstract

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 ClinV...

## Key facts

- **NIH application ID:** 10213298
- **Project number:** 1U54NS117170-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Lori L. Isom
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $50,418
- **Award type:** 1
- **Project period:** 2020-09-15 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10213298

## Citation

> US National Institutes of Health, RePORTER application 10213298, Project-005 (1U54NS117170-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10213298. Licensed CC0.

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