| Title: | Increase accuracy of disease risk prediction by combining the effect of polygenic risk and monogenic risk |
| Lead Institution: | Genoplan Korea Inc. |
| Principal investigator: | Mr Joon Ho Kang |
Application 72128
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About
Our research aim is to develop a disease predicting model to enable screening or preventive therapies for an individual at high risk complex disease. We expect to develop a prediction model by integrating various kinds of genetic and environmental factors. By combining these factors, we thus increase the accuracy of the disease prediction model. We also seek to reveal the ethnic difference of disease risk by comparing the model with our previously constructed model based on East Asian data. The research is expected to be complete in 3 years. Identifying the high risk individual for a given disease is a key need for precision medicine. This project will provide an explanation of causal factors for the complex disease. This in turn will help to early detect high risk individuals and reduce the public health burden.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 13258 | Polygenic risk and rare variant gene clustering enhance cancer risk stratification for breast and prostate cancers | Joon Ho Kang (+5) | 2024 | Communications Biology |
| 12019 | Stacked neural network for predicting polygenic risk score | Sun bin Kim (+4) | 2024 | Scientific Reports |
Enabling scientific discoveries that improve human health