Varun Yalavarthi
Research Mentor(s): Andrea Thompson
Mentor Department: Department of Internal Medicine/Cardiovascular Division
Authors: Varun Yalavarthhi, Keely Weber, Samanth Nichols, Ulla Lilienthal, Andrea Thompson
Session: Session 1 (9:00am – 9:50am)
Presentation Type: Poster 15
Abstract
With respect to Hypertrophic Cardiomyopathy, it has always been difficult to pinpoint the pathogenic mutations that cause disease. However, with the development of recent algorithms including AlphaFold, AlphaMissense, STRUM, and more, the field of predicting the pathogenicity of mutations has dramatically improved, as these programs allow us to predict protein structure, stability, and therefore the significance of certain mutations. Still using different prediction softwares for a given mutation may lead to conflicting results. By comparing the predictions of pathogenicity for mutations of the MYBPC3 protein for two programs, STRUM and AlphaMissense, we were able to plot a graph comparing how these two programs predicted the pathogenicity of a large dataset of mutations. Both programs would output a numerical result for each mutation (rapidly analyzing over 20000 mutations) and this number would tell us if the program predicted the mutation to be pathogenic or not. Using this dataset, we were able to calculate an odds ratio of 7.1130, telling us that to a decent extent, there is a correlation between the two programs, and that when AlphaMissense predicts pathogenicity for a certain mutation, then STRUM becomes more likely to also predict pathogenicity for that mutation as well. Overall, the comparisons between these two systems gives us better opportunities for predicting the pathogenicity of mutations of uncertain significance. We have supplemented this computational work with experimental evaluation of MYBPC3 cellular localization and stability.
