The 2019 QUEX PhD candidates are working on the following projects. Please note, these positions have been filled.

18. Using genetics to understand the interaction between BMI and physical activity and risk of obesity and type 2 diabetes

UQ academic lead

Professor Peter Visscher, Professorial Research Fellow, Institute for Molecular Bioscience, and Affiliate Professor, Queensland Brain Institute

Exeter academic lead

Dr Andrew Wood, Research Fellow in Statistical Genetics, University of Exeter Medical School

Project description

Obesity is the single greatest risk factor for type 2 diabetes. In the absence of a solution it is vital we understand more about the different factors that influence it and who is susceptible. The PhD candidate will develop and use extensive data analytical skills to understand the interplay between genes and physical activity and their effects on BMI and diabetes. More specifically, the student will test the hypothesis that different measures, types, patterns and frequencies of physical activity attenuate the genetic risk of obesity and type 2 diabetes. The student will use genetic variants associated with BMI, diabetes, and other metabolic traits identified through the largest genome-wide association studies (>1 million samples) to test this hypothesis.

This PhD opportunity will enable the candidate to develop knowledge and skills in the field of complex trait genetics, including the ability to handle large genetic- and accelerometer datasets, and develop statistical skills in the analysis of genetic-, cross-sectional and longitudinal data. The student will use by far the largest study with both genome wide genetic data and objective, accelerometer based measures of physical activity – 103,000 people in the UK Biobank study who have worn an accelerometer for 24 hours over 7 continuous days. Where previous studies have either relied on self-report activity, or were performed in much smaller studies, the student will have access to a variety of objective physical activity based measures already derived that define different amounts, types, patterns and frequencies of physical activity.

In health care systems with limited resources, this work will provide much-needed evidence for or against personalised approaches – for example, the evidence for targeting physical activity interventions at people with a stronger genetic predisposition to obesity and type 2 diabetes.

The PhD candidate will be based at the University of Exeter Medical School, UK, a world-class research institute for complex traits genetics and diabetes, under the direct supervision of Dr Andrew Wood, and supported by colleagues including complex-trait group leader Professor Tim Frayling. The candidate will also be supported by second supervisor Peter Visscher at the University of Queensland – a world leader in statistical complex trait genetics.