Parameter Trajectory Analysis to Identify Treatment Effects of Pharmacological Interventions

<p>The field of medical systems biology aims to advance understanding of molecular mechanisms that drive disease progression and to translate this knowledge into therapies to effectively treat diseases. A challenging task is the investigation of long-term effects of a (pharmacological) treatment, to establish its applicability and to identify potential side effects. We present a new modeling approach, called Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT), to analyze the long-term effects of a pharmacological intervention. A concept of time-dependent evolution of model parameters is introduced to study the dynamics of molecular adaptations. The progression of these adaptations is predicted by identifying necessary dynamic changes in the model parameters to describe the transition between experimental data obtained during different stages of the treatment. The trajectories provide insight in the affected underlying biological systems and identify the molecular events that should be studied in more detail to unravel the mechanistic basis of treatment outcome. Modulating effects caused by interactions with the proteome and transcriptome levels, which are often less well understood, can be captured by the time-dependent descriptions of the parameters. ADAPT was employed to identify metabolic adaptations induced upon pharmacological activation of the liver X receptor (LXR), a potential drug target to treat or prevent atherosclerosis. The trajectories were investigated to study the cascade of adaptations. This provided a counter-intuitive insight concerning the function of scavenger receptor class B1 (SR-B1), a receptor that facilitates the hepatic uptake of cholesterol. Although activation of LXR promotes cholesterol efflux and -excretion, our computational analysis showed that the hepatic capacity to clear cholesterol was reduced upon prolonged treatment. This prediction was confirmed experimentally by immunoblotting measurements of SR-B1 in hepatic membranes. Next to the identification of potential unwanted side effects, we demonstrate how ADAPT can be used to design new target interventions to prevent these.</p>

Associations of Fatty Acids in Cerebrospinal Fluid with Peripheral Glucose Concentrations and Energy Metabolism

Rodent experiments have emphasized a role of central fatty acid (FA) species, such as oleic acid, in regulating peripheral glucose and energy metabolism. Thus, we hypothesized that central FAs are related to peripheral glucose regulation and energy expenditure in humans. To test this we measured FA species profiles in cerebrospinal fluid (CSF) and plasma of 32 individuals who stayed in our clinical inpatient unit for 6 days. Body composition was measured by dual energy X-ray absorptiometry and glucose regulation by an oral glucose test (OGTT) followed by measurements of 24 hour (24EE) and sleep energy expenditure (SLEEP) as well as respiratory quotient (RQ) in a respiratory chamber. CSF was obtained via lumbar punctures; FA concentrations were measured by liquid chromatography/mass spectrometry. As expected, FA concentrations were higher in plasma compared to CSF. Individuals with high concentrations of CSF very-long-chain saturated FAs had lower rates of SLEEP. In the plasma moderate associations of these FAs with higher 24EE were observed. Moreover, CSF monounsaturated long-chain FA (palmitoleic and oleic acid) concentrations were associated with lower RQs and lower glucose area under the curve during the OGTT. Thus, FAs in the CSF strongly correlated with peripheral metabolic traits. These physiological parameters were most specific to long-chain monounsaturated (C16∶1, C18∶1) and very-long-chain saturated (C24∶0, C26∶0) FAs. Conclusions: Together with previous animal experiments these initial cross-sectional human data indicate that central FA species are linked to peripheral glucose and energy homeostasis