| Title: | Use of UK Biobank genetic data to support drug discovery and development |
| Lead Institution: | Bayer Aktiengesellschaft |
| Principal investigator: | Dr Daniel Freitag |
Application 28807
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About
The study of human genetic variation is an emerging paradigm for anticipating target-related disease-relevance, [including safety and efficacy, i.e. the therapeutic window]. We aim to use UK Biobank data to identify and validate new drug targets for diseases within the research interest of Bayer, which includes diseases of the eye, the cardiovascular, respiratory and reproductive organ systems, as well as various types of cancers, e.g. in Immunooncology, we are also interested in autoimmune, immunological and chronic inflammatory conditions. In addition , we would like to explore combinations of genetic and non-genetic patient characteristicss to better understand and stratify disease sub-phenotypes. The proposed research aims to identify new ways to understand the disease biology, to develop therapies better matching to still un-met medical needs in subpopulations of patients. Hence this research meets UK Biobank?s purpose by improving the prevention and treatment of illness. We plan to do three primary types of analyses: 1) genetic association analyses of patient groups versus controls within UK Biobank 2) genetic association analyses of UK Biobank controls with external patient populations and 3) analyses of broad phenotypic consequences of variants related to targets of interest (PheWAS). We request access to the full cohort of ~500,000 individuals.4 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 12326 | Deep learning on resting electrocardiogram to identify impaired heart rate recovery | Nathaniel Diamant (+21) | 2022 | Cardiovascular Digital Health Journal |
| 12414 | Genetic and environmental determinants of diastolic heart function | Marjola Thanaj (+16) | 2022 | Nature Cardiovascular Research |
| 9041 | Leveraging Human Genetics to Estimate Clinical Risk Reductions Achievable by Inhibiting Factor XI | Benjamin Georgi (+10) | 2019 | Stroke |
| 9552 | Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism | Yurong Cheng (+13) | 2021 | Nature Communications |
Enabling scientific discoveries that improve human health