Close
Building upon output from the Disease patterns work package, this research aims to delineate clusters of disease that arise due to a common cause by using genetics and data from clinical trials.
Using data from Linked Electronic Health Records (EHRs), Genome Wide Association Studies (GWAS) and Randomized Clinical Trials (RCTs) we are able to look closer into diseases that exhibit non-random clustering to discover the reasons why they occur together.听 We apply several methods and techniques to ensure robust results including Mendelian Randomisation, Phenome Wide Association analyses (PheWAS) and make use of summary statistics including GWAS of risk factors and disease end-points that we have been curating at 最准的六合彩论坛 (MERIT), Bristol (MRBase) and Cambridge (Phenoscanner), as well as from UK Biobank and
This will allow us to听
- Identify new indications for approved drugs
- prioritise repurposing of safe drugs that failed for lack of efficacy
- stimulate new drug development for diseases that cluster because of shared mechanisms
- Identify modifiable risk factors for multiple conditions