In vivo and in silico dynamics of the development of Metabolic Syndrome - Rozendaal, Yvonne J. W.; Wang, Yanan; Paalvast, Yared; Tambyrajah, Lauren L.; Li, Zhuang; Willems van Dijk, Ko; Rensen, Patrick C. N.; Kuivenhoven, Jan A.; Groen, Albert K.; Hilbers, Peter A. J.; van Riel, Natal A. W. (PLOS Computational Biology, 2018)
Author summary Obesity is becoming a growing health problem, with the risk of running into a disease state called the Metabolic Syndrome (MetS). It is difficult to study MetS in humans as it develops over a long period of time while many processes and organs are involved. Moreover, each patient may present itself with different characteristics. We combined data from animal experiments with a computer model and computer simulations to study the development of MetS. The new model correctly predicts which changes in the underlying metabolic processes could explain the MetS symptoms. Unexpectedly, two different subgroups were identified: those with high cholesterol and high triglycerides, and those without. The computer model found that in those who develop lipid abnormalities, both dietary cholesterol absorption and hepatic liver fluxes were higher.