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Background

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease in high-income European countries and the US, affecting around 30% of the population, with the prevalence increasing in-line with the growing epidemic of obesity and diabetes1. NAFLD is independently associated with the development of type 2 diabetes and cardiovascular disease. Why the liver begins to accumulate fat is not known; more research is needed to elucidate the underlying causes of intrahepatic fat storage in order to identify ways of preventing and treating NAFLD.

There is now evidence demonstrating that the nutrient composition of our diet, especially fat composition, can influence the accumulation of fat within the liver. However, the physiological mechanisms of intrahepatic fat accumulation are not well understood, and associations between dietary intake and liver fat have not been documented reliably at the population level.

To answer questions on how diet composition may affect the regulation of liver fat content, we would like this DPhil project to take an interdisciplinary approach: we want to use big data analytics on large epidemiological studies such as the UK Biobank that have recorded liver MRIs in ~50,000 adults, to inform the design of human dietary intervention studies  incorporating stable isotope tracer methodologies to investigate whole-body and intrahepatic fatty acid metabolism.  

Project Aim: To document potential associations between dietary fat intake and liver fat in UK Biobank, and then explore these potential associations in more detail by working on an in-vivo human physiological study.

1 N Engl J Med 2010;363:1341-50.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The student will be provided with training in statistical and epidemiological methods, and writing academic papers for peer-reviewed journals. Half of this DPhil project will be spent in NDPH learning how to analyse large epidemiological studies such as UK Biobank. The other half of this DPhil project will be spent in OCDEM where the student will learn how to design and execute detailed in vivo human physiological studies.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

Both departments have excellent computational facilities, infrastructure and a strong interdisciplinary team with expertise in physiology, epidemiology, statistics, nutrition, clinical medicine and biochemistry. NDPH hand OCDEM have regular seminars and workshops, and strongly support attendance at meetings to present research findings and develop further expertise.

Prospective candidate

A candidate with a background in biological sciences or nutrition would be well suited to this project. Experience running statistical analyses would be an advantage, but training will be provided. 

Supervisors