Mathematical modeling of fatty acid metabolism during consecutive meals and fasting : New insights into fatty acid regulation based on arterio-venous data

Abstract: Obesity, type 2 diabetes, and cardiovascular diseases are major problems in today's society, causing millions of deaths every year. One of the main risk factors for these diseases is a dysregulation of the fatty acid metabolism, where the balance between release and uptake of fatty acids is disturbed. Thus, understanding how fatty acid metabolism works is of great importance in the battle against these diseases. The human fatty acid release and uptake can be unraveled by measuring the difference in metabolite concentrations between an artery before the adipose tissue and a vein draining the tissue. Such measurements are called arterio-venous. However, due to the complexity of the fatty acid mechanisms, the resulting measurements alone are not enough to understand all of the involved reactions governing the metabolism. One analytical tool to decipher such complex mechanisms is mathematical modeling. A few mathematical models have previously used arterio-venous data of the fatty acid metabolism, but none of the previous models describe a full day including several meals and nightly fast. In this project, I combine mathematical modeling and arterio-venous data to investigate the mechanisms of fatty acid metabolism during three consecutive meals and fasting. The resulting mathematical model can explain arterio-venous data of free fatty acids, triglycerides, and glycerol. The model predictions show that re-esterification of monacylglycerides, a mechanism that has not been considered before when analyzing arterio-venous data, is of importance to be able to accurately describe the fatty acid metabolism. Additionally, the model predicts that there is a hormonal regulation during the night. Finally, it is shown that many of the previous simple calculations used to approximate metabolic reactions do not capture the desired reactions but instead calculate more complex properties, while the use of the model allows for a more detailed analysis separating all of the different reaction rates. These results give new insights into the complex mechanisms of fatty acid metabolism and provide a new tool to analyze arterio-venous data more comprehensively. In the future, this can lead to a better understanding of metabolic diseases such as obesity, type 2 diabetes, and cardiovascular diseases.