This project is offered as part of the University of Dundee 4-year MRC DTP Programme “Quantitative and Interdisciplinary approaches to biomedical science”. This PhD programme brings together leading experts from the School of Life Sciences (SLS), the School of Medicine (SoM) and the School of Science and Engineering (SSE) to train the next generation of scientists at the forefront of international science. The outstanding biomedical research at the University of Dundee was recognised by its very high rankings in REF 2014, with Dundee rated as the top University for Biological Sciences in the UK. A wide range of projects are available within this programme crossing exceptional strengths in four key areas: Infection and Disease; Responses to Cellular Stresses; Development, Stem Cells and Neurobiology; and Big Data and Translation. All students on this programme will receive training in computational biology, mathematical biology and statistics to equip with the quantitative skills in tackling complex biological questions. In the 1st year, students will carry out 3 rotation projects prior to selection of the final PhD project.
There is overwhelming evidence that inflammation contributes to the development of cardiovascular disease (CVD) but counterbalancing this is evidence from meta-analysis of randomised control trials that many existing anti-inflammatory drugs, such as COX2 inhibitors and anti-TNF drugs, tend if anything to exacerbate risk of CVD. If inflammation is to be targeted successfully in CVD, new paradigms of drug action and new approaches to patient selection need to be generated. Our recent work has been on metformin, which in observational studies also reduces risk of CVD. Our work in this area has established that anti-inflammatory effects of metformin are exerted irrespective of diabetes status [1, 2], through poorly understood ‘immunometabolic’ mechanisms that are different from existing anti-inflammatory drugs and which we have recently found are accompanied by changes in amino acid homeostasis. Better understanding of these effects is likely to have a high-impact, by supporting better stratification and targeting of repurposing trials of metformin in non-diabetic CVD . To ensure relevance to human disease, it is desirable to extend our studiesfrom rodent-derived cells to include human-derived cells. To do this, the student will identify and then use a suitable human cell model to investigate the relationship between amino acid metabolism and immune effects of the drug. This will include evaluation of immortalised cell lines, such as U-937, HL-60 or THP1, to identify combinations of cells/ stimuli suitable for further study. Combination of data from human cell studies with (mouse) knockout cells from our network of collaborators and with biomarkers in human plasma stored from previous clinical trials, as well as exploitation of state-of-the-art patient databases, provides the student with an outstanding platform to establish high-impact translational cross-validation of clinical observations withcell/molecular findings, as demonstrated in our highly interdisciplinary recent work [1, 2].
Recent work from the lab can be found in the following references:
1. Rena, G. and C.C. Lang, Circulation 2018. 137: p. 422-424.
2. Cameron, A.R., et al., Circ. Res., 2016. 119: p. 652-665.