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Approved Research

Discovery of genetic interactions associated with human diseases

Principal Investigator: Professor Chad Myers
Approved Research ID: 64016
Approval date: January 14th 2021

Lay summary

Scientific rationale: Although genomic technology enables efficient sequencing of human genomes, we are still not able to accurately predict disease states from genome sequence. Our research has shown that a major component of the inability to interpret information in our genomes likely stems from complex genetic interactions. Some genes only result in disease when combined with other genes. The current paradigm for interpreting genetic data focuses on identifying single variants contributing to each disease of interest, and thus, these approaches largely fail to identify cases where multiple mutations in an individual's genome cause disease.

Aims: Our group has recently developed a novel computational approach called BridGE, which leverages insights from large-scale studies of genetic interactions in model organisms, to discover genetic interactions in humans. This approach overcomes a fundamental statistical challenge that previously limited progress in understanding genetic interactions and can provide a new lens for interpreting hundreds of existing collections of genetic data. In this project, we will focus on extending and applying this approach to different diseases and establish a systematic collection of high-confidence genetic interactions associated with different diseases. We will also develop new computational methods for identifying specific genes and mutations that are high priority for further experimental validation and, in the long term, potential targets for new therapeutics.

Project duration: This will be an ongoing project.

Public health impact:  New insights about the complex genetic mechanisms behind different diseases could have a major impact on the genetic disease research community. For example, knowledge of pathways that, when perturbed, modulate disease risk, is the first step toward identifying new therapeutic avenues for treating disease. Furthermore, knowledge of disease-associated genetic interactions could define new, previously unappreciated subtypes of the disease that are amenable to early detection and prevention or respond to targeted therapeutics.