The field of personalised medicine is being transformed by the use of whole genome technology. We are currently studying a population of 9000 individuals with type 2 diabetes to determine the genetic factors in determining their response to a wide range of commonly used drugs such as the statin family of cholesterol lowering drugs and anti-clotting agents such as aspirin. The use of these drugs may be limited by side effects such as muscle pain, in the case of statins, and stomach bleeding in the case of aspirin. We have performed a whole genome scan in 8000 individuals with type 2 diabetes and have imputed this to 50 million SNPs from the 1000 Genome project. Our group is currently assessing the role of these variants in determining both the efficacy and susceptibility to side effects of such drugs. This is a major statistical and bioinformatics challenge and it is clear that many gene variants contribute to an individual’s response. It is hoped that this research will provide useful information to guide the treatment of individual patients to maximise the benefit of treatment while minimizing potential side effects.
The aim of this PhD project will be to determine groups or networks of genetic variants that combine to determine responses to drugs and ultimately cardiovascular outcome. The student will develop skills in bioinformatics related to molecular pathway analysis and high throughput genetic analysis, with an emphasis on computational skills including the handling of large datasets and statistical modelling.