Improving polygenic risk scores derived from summary statistics of genome-wide association studies
Scientific rationale: Individuals of different genetic makeup have different predispositions to diseases. For example, women carrying the pathogenic alleles in BRCA2 are more likely to develop breast cancer. Some psychiatric diseases including bipolar disorder and schizophrenia are known to be driven by more genetic variants. Therefore, the human diseases could be predicted with the genetic information to a large extent.
Aim: In this project, we will develop a predictor for disease risk calculation from personal genome information. Basically, it calculates a value between 0 and 1, measuring how likely an individual of specific genetic makeup can develop certain disease. The risk prediction can be put into clinal usage for precision prevention, screening and diagnosis, and treatments.
Public health impact: Accurately predicting disease risk will facilitate disease prevention and treatment. For example, individuals with high risk of a particular disease can be advised for a healthy lifestyle and more frequent examinations. Personalized therapies can be conducted by clinicians.
Project duration: We plan to complete the project in three years.