Analysis of dynamic adaptations in parameter trajectories to identify treatment effects of pharmacological interventions

Objective An approach is presented to integrate treatment-in-time data and evaluate the long-term effects of pharmacological interventions. ADAPT (Analysis of Dynamic Adaptations in Parameter Trajectories) uses the concept of time-dependent evolution of model parameters. Methods Data from longitudinal intervention studies are integrated in a computational model of hepatic lipid and plasma lipoprotein metabolism (Tiemann et al. PLoS Comput Biol. 2013, 9(8):e1003166). Dynamic changes in the model parameters are identified to interconnect the individual time points. These parameter trajectories describe the dynamics of molecular adaptations underlying the treatment response. Hereby the regulatory effects caused by interactions of the metabolome with the proteome and transcriptome are captured. Results 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. Time-dependent parameter trajectories were generated to study treatment response over a time period of 3 weeks. Changes in transporter and enzyme activities were identified, which explained the observed changes in the metabolic profile. Counter-intuitive predictions about the dynamics of molecular adaptations have been experimentally verified. Conclusions ADAPT provides insight into the affected biological systems and identifies molecular events that should be studied to unravel the mechanistic basis of treatment outcome. To start to understand the inverse association between HDL cholesterol ("good cholesterol") and cardiovascular risk it is important to focus on the HDL fluxes instead of the HDL plasma levels.