PhD studentship University of Edinburgh
Application deadline 5pm on 23rd March 2017
PhD Project: Improving prediction of the complications of type 2 diabetes
Supervisors: Prof Jackie Price & Prof Christopher Weir
Centre/Institute: Usher Institute of Population Health Sciences and Informatics, University of Edinburgh
More information/to apply:
E-mail Jackie.Price@ed.ac.uk
Background
We are currently reaching an epidemic of type 2 diabetes, with patients living longer and developing complications which affect longevity and quality of life. There is an urgent need to develop accurate methods of predicting who will and who won’t develop complications, so that targeted preventive measures can be instituted without over-intervention in healthy individuals. Such complications include macrovascular disease (heart attacks and strokes), kidney dysfunction, eye disease/retinopathy and cognitive impairments such as memory loss. As an emerging approach for disease prediction and prevention, as well as treatment, the application of the research techniques employed within Precision Medicine (including analysis of high density ‘-omics’ data alongside more traditional physical and circulating risk markers), in well-phenotyped, longitudinal cohorts, is ideal for addressing this research need.
Data resource available: The student will be given unrestricted access to the Edinburgh Type 2 Diabetes Study (ET2DS), which includes serial data (4 time-points over 10 years) on a wide range of clinical variables, retinal images, stored blood and urine and record linkage to routine hospital discharges for over 1000 men and women with type 2 diabetes1. The ET2DS is one of the original cohorts within ‘UCLEB’, the University College-London School-Edinburgh-Bristol consortium of highly phenotyped population-based prospective studies, which focuses on cardiometabolic, genetic and metabolomic risk factors for vascular disease2. This initiative is integrating genotype, biomarker and disease data to uncover disease mechanisms and potential therapeutic targets and utilises high density genotyping (focusing on cardiometabolic diseases, rare variants and drug-targeting) and imputation against the 1000 genomes European ancestry reference metabolomics data. The student will be able to access UCLEB data to augment power and/or provide a replication cohort for the ET2DS, and will also be able to extend their analyses to include genetic proxies for vascular biomarkers.
Aims
The student will address one or more specific research questions, potentially leading to the development of risk ‘scores’ for complication(s) of interest based on (1) identification of ‘novel’ circulating cardiometabolic biomarkers, using analysis of high resolution metabolic phenotype data (from high-throughput 1H-nuclear magnetic resonance (NMR) spectroscopy platform3) a platform including 228 circulating low molecular weight metabolites and lipids/lipoprotein subfractions, (2) combination of sub-clinical markers of vascular disease with ‘traditional’ vascular biomarker profiles (obesity, inflammation etc). The development of sub-clinical measures of vascular disease can precede the onset of diabetes-related vascular complications by years and may help to establish a high risk profile for affected individuals (such measures are available from baseline in the ET2DS, including ankle brachial index, pulse wave analysis of arterial stiffness, carotid IMT/plaque, retinopathy).
Training Outcomes
The student will be trained in advanced computational, statistical and epidemiological methods as applied to hypothesis-driven research of public health importance. They will benefit from the epidemiological (JP) and statistical (CW) expertise of the supervisors as well as wide-ranging methodological expertise from senior members of the Usher Institute molecular epidemiology research group. They will also have access to methodologists using cutting-edge ‘-omics’ analysis techniques within the UCLEB consortium and to cross-disciplinary researchers (including metabolic and renal clinicians, psychologists and human geneticists) who form the large team of ET2DS investigators, collaborators and other researchers.
References
- Price JF, Reynolds RM, et al. The Edinburgh Type 2 Diabetes Study: study protocol. BMC Endocrine Disorders, 2008; 8: 18
- Shah T, Engmann J, et al. Population Genomics of Cardiometabolic Traits: Design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium. PLoS ONE 2013; 8(8): e71345
- Ala-Korpela M. Critical evaluation of 1H NMR metabonomics of serum as a methodology for disease risk assessment and diagnostics. Clin Chem Lab Med, 2008; 46: 27-42
