Skip to navigation Skip to main content Skip to footer

Approved Research

Develop statistical genetic methods with hidden subgroups

Principal Investigator: Professor Wei Li
Approved Research ID: 78898
Approval date: January 26th 2023

Lay summary

In this study, we will develop novel methods to identify who (which subgroup of people) have a higher risk of diseases (e.g., breast cancer) than others.

Previously, scientists have shown that some humans are born with variations in their DNA (known as "risk variants") that increase their lifetime risk of some diseases (e.g., breast cancer). Using these risk variants, scientists defined the polygenic risk score (PRS) to predict if a person will have a high risk to have a certain disease (e.g., breast cancer). However, previous studies do not consider the difference between people. In this study, we will develop novel methods, which will take into account population differences, to obtain more accurate disease risk predictions.

We will mainly focus on brain diseases and breast cancer first. And if promising, our methods will be extended to other human diseases. The whole project is expected to last for about three years.

We believe that our study will make significant contributions to disease (e.g., breast cancer and brain diseases) risk prediction. From a public health perspective, if we can identify the subgroup of people who have high disease risk, then we can provide appropriate care for them.