| Title: | Integration of genomic data from UK Biobank and other omics data to diagnose, predict, understand and inform treatment of diseases |
| Lead Institution: | Central South University |
| Principal investigator: | Dr Hong-Mei Xiao |
Application 63047
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About
Although existing researches, such as genome-wide association studies (GWASs), have get many successes in identifying genetic variation of bone-related diseases, most of biologic mechanism between the genetic variation and diseases are generally not understood. In addition, it is still a challenge to utilize genomic information to diagnose diseases. New powerful and robust statistical methods are still pressing need for prediction, diagnosis and identifying new treatment for bone-related diseases. In this study, we have 3 main aims: First, we will construct prediction models to diagnose or predict individual's risk of bone-related diseases, using genomic data and other clinical risk factors from UK Biobank. Second, we will integrate genomic data from UK Biobank and other omics data to reveal the biological mechanism of bone-related diseases. Third, we consider developing a system biology approach to identify potential drug candidates for human diseases. The project period will be maximally 36 months. This research might potentially construct a new way to accurately predict the risk of complex diseases, identify some novel putative biological mechanism effecting complex diseases and identify new potential drug candidates for human diseases. All these findings will help us improve the diagnosing and treatment of human diseases.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 13049 | Variability in performance of genetic-enhanced DXA-BMD prediction models across diverse ethnic and geographic populations: A risk prediction study. | Yong Liu (+12) | 2024 | PLOS Medicine |
Enabling scientific discoveries that improve human health