About the Project
Lead supervisor: Dr. Rachel Freathy, College of Medicine and Health, University of Exeter
Additional supervisors:
Dr. Richard Oram, College of Medicine and Health, University of Exeter
Dr. Michael Weedon, College of Medicine and Health, University of Exeter
Due to a major recent award, applications are invited from students wishing to further their scientific careers by undertaking a PhD in a diabetes related area of research. Up to six studentships will be fully funded from autumn 2019 with enhanced stipends funded from a new £6million award. This award reflects Exeter as a world renowned centre of excellence for diabetes research.
Students can select from any of the advertised 16 projects. These projects have been carefully selected to provide students with an excellent scientific training in an important area of diabetes research, the latest laboratory and computing skills, outstanding resources, and with world leading scientists as supervisors. They cover various aspects of diabetes research, including autoimmunity in the pancreas; neuro-endocrinology to understand the relationship between the brain, mental health and the endocrine system; gene regulation in the placenta and fetal development of the pancreas; rare genetic forms of diabetes; muscle physiology; and the use of electronic medical records to understand disease causes, treatments and progression. Students will learn a wide range of state-of-the-art techniques, which could include CRISPR-Cas9 gene editing, DNA methylation, DNA sequence analysis, muscle insulin sensitivity physiology, brain electrophysiology, medical statistics, R for statistics and data visualisation and programming in python, data science including machine learning, in vivo metabolic phenotype skills and cell biology including 3D stem cell culture. Students will have access to outstanding resources, including cohorts of >5000 patients with rare defects in insulin secretion, a world leading collection of samples for study of pancreas pathology, resources of electronic medical records and biobanks from millions of people and unique resources for studying human development of the pancreas and brain.
Project description:
This studentship will use genetic data on mothers, fathers and children to investigate the influences of genetics and the intrauterine environment on offspring susceptibility to Type 1 diabetes. The student will develop computational, bioinformatics and statistical skills.
In observational epidemiology, there is a robust and well replicated observation that maternally-inherited genetic susceptibility to Type 1 diabetes carries a lower risk of offspring disease than paternally-inherited susceptibility. However, this has not been tested using genetic risk scores. In addition, there are several observational associations between maternal factors and offspring susceptibility to Type 1 diabetes, including maternal autoantibody status and non-inherited maternal diabetes risk. Additionally, higher maternal BMI, higher birthweight, and lower maternal vitamin D are associated with higher risk to offspring. However, the causal nature of these associations is not known.
The student will use maternal, paternal and offspring genetic data from several large, family-based studies to investigate the above.
This project will enable the student to develop expertise in cutting-edge techniques to assess causality in epidemiology studies using large SNP array datasets. They will gain experience and training in the use and modelling of large genotyping array datasets, generation of genetic risk scores for autoimmune disease, genetic epidemiology including mendelian randomization, and the biology of autoimmunity in early life.
The student should be enthusiastic about data, statistics and genetics – s/he will learn a wide range of data handling and analysis skills, including basic computer script writing, bioinformatics and statistics. The student will join a vibrant, diverse and interdisciplinary research team, including geneticists, mathematicians, computer scientists and clinicians, all studying aspects of diabetes and related conditions.
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