Leveraging predictive models to design high-throughput assays to resolve variants of uncertain significance (VUS) in SYNGAP1

MDBRSYNGAP

Feb 1

Awardee: Gemma Carvill

Institution: Northwestern University

Grant Amount: $61,222.00

Funding Period: February 1, 2024 - January 31, 2025

Summary:

SYNGAP1-related disorder is caused by pathogenic (disease-causing) loss of function variants, and while most variants described to date are truncations, there are also at least 50 pathogenic missense variants that have been described. However, missense variants are more likely to be classified as uncertain significance i.e. of unknown impact on protein function, we call these VUS. This is because of the difficulties with predicting whether these variants impact SYNGAP1 function using current tools. Here we will use a computational approach to determine what characteristics of missense variants are more likely to impact SYNGAP1 function. We will then design and test a method/assay based on this characteristic to identify pathogenic missense variants. This method will be able to screen hundreds of missense variants at a time. We will make this data available in an accessible manner to the patient community.

MDBRSYNGAP2023-1

Million Dollar Bike Ride

Leveraging predictive models to design high-throughput assays to resolve variants of uncertain significance (VUS) in SYNGAP1

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