Identifying ways to predict a person’s risk of cardiovascular disease
Professor Dr Aroon D Hingorani (lead researcher)
University College London
Start date: 01 July 2014 (Duration 3 years)
Cardiometabolic disease prediction, causal analysis and drug development using high-resolution 1 H- nuclear magnetic resonance (NMR) metabolomics (The UCLEB consortium)
A BHF-funded consortium bringing together top researchers from University College London, London School of Hygiene and Tropical Medicine, University of Edinburgh, and the University of Bristol is analysing blood samples for a huge range of molecules that are present in the body and perform important functions. These molecules include fats and proteins that are important for normal bodily processes such as our metabolism. This analysis could provide important clues on the causes of heart and circulatory disease, which could be used to predict a person’s risk of disease. The consortium has previously worked hard to obtain blood samples from over 13,000 volunteers. Now, the BHF has pledged a further £800,000 worth of funding to analyse all these samples. They are looking to see which combinations of molecules, or changes to molecules, might cause disease. They will use a sophisticated research technique called nuclear magnetic resonance spectroscopy, which enables large numbers of molecules to be analysed quickly. The large amount of data generated will enable the researchers to identify particular molecules of interest that might be linked to a higher risk of developing heart disease. It might also help identify people at most risk so they can be monitored or treated more effectively. Identifying the molecules responsible for heart and circulatory disease will greatly aid the development of new medicines to target those molecules that may be having a damaging effect.
Project details
Grant amount | £854,987 |
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Grant type | Chairs & Programme Grants |
Application type | Special Project |
Start Date | 01 July 2014 |
Duration | 3 years |
Reference | SP/13/6/30554 |
Status | Complete |