Functional interpretation of complex disease traits by TWAS
Approved Research ID: 63757
Approval date: January 25th 2021
Genome-wide association studies (GWAS) have successfully identified many genetic variants associated with complex diseases. Despite this success, the mechanism in which the genetic variants contributes to the risk of disease is often not clear. One of the reasons is that the genetic variants increase or decrease the risk by altering the production amount of a certain protein, but not the function. Measuring protein amount is technically challenging, and therefore the expression of mRNA, the intermediate product, has been used as a good indicator of protein production. There is a method to predict the tissue-specific effect of genetic variants on mRNA expressions. The predicted mRNA expression can be used to identify genes whose genetically-defined expression is associated with disease risks.
We are planning to use such technologies on the UK Biobank data to predict the mRNA expressions on human tissues of complex diseases, and detect associations between predicted expression and various phenotypes to identify novel therapeutic targets and biomarkers. We also compare the genetically defined expression profile with actual expression profiles in public repositories to differentiate whether the difference between cases and controls can be attributed to genetic (i.e. genetic risk factor) or environmental (i.e. environmental risk factor or disease outcome) factors. As this approach would help to distinguish whether the dysregulation is the cause or the outcome, it would provide more insights into the disease mechanisms. Through the functional interpretation of causal genetic variants for the alteration of mRNA expressions, this approach may allow us to identify the druggable targets for therapeutic intervention and develop disease modifying therapies for complex diseases.