Constructing a genetic effect network to predict polygenic disease risk
Principal Investigator: Mr Austin Conklin
Approved Research ID: 60468
Approval date: May 29th 2020
Coronary artery disease (the primary cause of heart attack) is heritable. Currently, geneticists are working on methods to predict whether or not someone will develop coronary artery disease based on that person's genetic makeup. We aim to improve on those methods using data from a large study of human tissues. The study measures gene 'expression' (how active a certain gene is) in a given tissue and determines which genetic variants cause changes in expression. An import finding from this study (and from many other such studies) is that a genetic variant changes gene expression differently depending on which tissue you measure its effect in. We aim to take this tissue-specific manifestation data and use it to improve prediction scores. The rationale for this is that some genetic variants have a big effect on some tissues but not others; current risk predictors in the field are agnostic to this fact. We believe that combining tissue-specific genetic effects and risk prediction will allow us to predict a person's coronary artery disease risk more accurately. That way, people at high risk can be prescribed drugs to mitigate the development of heart disease. We plan to work on this project for the next two years.