The role of chain length in fatty acid uptake in both health and disease: a combined experimental-theoretical modelling approach

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Heart disease, type 2 diabetes and obesity (collectively known as metabolic syndrome) are three of the most serious health conditions facing the UK today. They affect one in four adults in the UK, costing the NHS over £10 billion annually. These figures are rising rapidly, with 1 in 2 people predicted to be affected by 2050, with an associated cost of £50 billion. Sadly, we do not know the basic mechanisms of how type 2 diabetes (and many other obesity-related conditions) occur. Establishing the mechanics and role of fats is critical since too many entering our cells can contribute to the development of diabetes. This then poses the question: how do fats enter cells? At present, we know very little. Identifying how fats enter cells will pave the way for the development of new diets and drug treatments to reduce fat uptake. In the long term, this will help to slow and potentially halt the development of type 2 diabetes, obesity and heart disease.I will use imaging techniques to measure how much fat crosses into cells, how quickly this happens, and how this changes with different types of fats. I will then use this information to build mathematical models that explain the mechanisms behind fat uptake. Although it may seem surprising that mathematics can be used to answer questions in biology, recent progress has shown that combining these two areas can lead to great advances in physiology and medicine. In this project, I will take advantage of my mathematical model to make predictions about the ways in which fats enter cells. I can then confirm or reject these predictions through experiments in the lab. With a good understanding of fat uptake, I will be able to start testing drug treatments and diets in rodents to prevent the progression of type 2 diabetes and obesity.