Obesity is a major driver of ill-health and is associated with numerous complications, such as diabetes. Obesity is typically defined by Body Mass Index (BMI) which measures an individual’s weight while taking into account their height. This measure, though useful and easy to calculate, can greatly under- or over-estimate an individual’s liklihood of developing obesity-related complications. This is because BMI does not consider the numerous differences in the body fat composition that exist between individuals. Recent research has begun to show that the accumulation of fat in unusual locations, such as the liver, pancreas, and muscle, is particularly high in individuals at a high risk of diabetes.
In a new multi-year study of the UK Biobank cohort, we aim to investigate the predictability of future fat accumulation, focusing on accumulation in the liver, pancreas, and muscle tissue, which all have previously been linked to metabolic risk. This novel study will make use of longitudinal imaging data which allows the direct measuring of changes in levels of ectopic fat across time in a large cohort of individuals. From these quantified changes, we will aim to predict an individual’s current risk of fat accumulation in specific high-risk depots using clinical, laboratory, questionnarie, and genetic data. From identified depot-specific risk factors, we will further aim to investigate the biological mechanisms that lead to fat accumulation in specific depots.
Our research will aim to provide predictive models that could be used clinically to identify patients who are at a high risk of developing obesity-related complications so that they may be targetted for early intervention, even those who are not defined as obese by their BMI. Obesity is a significant public health concern as it is a significant driver of the development of multiple long-term conditions (MLTCs) in patients. Therefore, the ability to predict individuals who at at high-risk of complications could allow the possibility of prevention which would reduce the significant burden of patients with MLTCs which modern healthcare systems face. The insight gained into specific risk factors associated with the accumulation of fat in specific depots would further expand our knowledge of the biology of high-risk obesity which may lead to novel therapies for the treatment of unhealthy obesity.
To summarise, this research aims to provide predictive models of fat distribution and to provide insights into the mechanisms driving fat accumulation.