Pleiotropy and genetic risk prediction of complex diseases
Accurate genetic risk predictions of disease susceptibility can aid in tailoring disease risk assessment, diagnosis, and treatment to individual patients or subgroups from the population for improving health and healthcare. However, the current strategy to develop a risk prediction model only utilizes one disease outcome at a time. In reality, a genetic locus can be associated with multiple disease outcomes or traits; a phenomenon called pleiotropy. The overarching goal of this 3-year project is the development of new prediction methods that can use the pleiotropy effects from genome-wide genetic loci to improve the genetic risk prediction of cardiovascular diseases, psychiatric diseases, gastrointestinal diseases, neurological disorders, and cancers. The algorithms and software resulting from the project developments will be publicly released. Successful completion of the project will result in better disease risk stratification of individuals in the general population, which can lead to the improvement of disease diagnosis and treatments in the clinic.