| Title: | Multi-trait trans-ethnic genetic analyses |
| Lead Institution: | University of Oxford |
| Principal investigator: | Dr Robin Walters |
Application 50474
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
There is growing interest in the use of genetic data to inform clinical practice, helping to identify those at greatest risk of disease and, potentially, helping to more accurately identify the causes of disease and to prioritise treatment options. However, there is growing evidence that data from existing genetic analyses, collected primarily from Western populations, are not as useful for those from other ethnicities, with potential consequences for equality of access to healthcare provision. This project aims to better understand why genetic "risk scores" currently perform better in Western populations than in Chinese. We will investigate, across a wide range of traits and disease, in both UK Biobank and China Kadoorie Biobank, the extent to which different factors contribute to the poor performance of genetic risk scores in a trans-ethnic setting. In addition to detailed analyses focussed on particular combinations of risk factors and diseases (e.g. obesity and diabetes, blood pressure and stroke), we will systematically compare - across the full range of the available data - the patterns of the genetic contribution to disease and phenotype in each of the two ancestries. We will examine the extent to which results from one ancestry are predictive in other ancestries, investigate the similarities or differences between ancestries in the genetics underlying different diseases and risk factors, and determine whether there are consistent patterns between ancestries in terms of the groups of diseases and related traits which have shared genetics. This represents a comprehensive comparative investigation of the genetic architectures of disease and risk factors in two major biobanks. Depending on the success of funding applications, it is expected that the primary analyses will be complete within 3 years. Secondary analyses and more in-depth investigations of particular differences between ancestries will be subject of applications for extensions to this project or for separate projects. We anticipate that this project will provide a comprehensive understanding of the transferability of genetic risk scores between populations, potentially contributing to more effective "precision medicine" for everyone, irrespective of their ethnicity.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 9896 | Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes. | Pang Yao (+27) | 2024 | Diabetes Care |
Enabling scientific discoveries that improve human health