Abstract 443: ABCA1 Up-Regulation but Not CETP Inhibition is Predicted to Increase the Reverse Cholesterol Transport (RCT) Input Rate: a Simulation Study of HDL-C Raising Targets Using a Novel in-silico Model of Lipoprotein Metabolism and Kinetics

Introduction HDL is believed to mediate RCT and hence lower CV risk. The recent failures of HDL-C raising drugs to improve CV outcomes raise questions on the link between HDL-C and RCT. We investigate the association between the two using an in-silico model.

Methods The model describes the cyclic process of αHDL maturation from lipid-poor ApoA-I (pre-β1) and the regeneration of pre-β1 from αHDL particles via remodeling processes (e.g., particle fusion, SRB1 and CETP mediated lipid transfers). RCT is a complex process initiated by cholesterol efflux into plasma. In our model we assume that the ABCA1-dependent loading of cholesterol onto pre-β1 is the main contributor to cholesterol efflux and quantify this as the RCT input rate. The model is calibrated to literature data on normal and CETP deficient subjects and validated with data on ABCA1 deficiency. Using a virtual population of n=359 subjects with low HDL-C, we simulate two target modulations, 80% CETP inhibition and 100% ABCA1 up-regulation, chosen to raise HDL-C by comparable amounts.

Results Table 1 shows that both target modulations increase HDL-C by approximately 50%. For ABCA1 up-regulation, this reflects an increased RCT input rate; while for CETP inhibition, the increase in HDL-C results from a decreased clearance rate. The model also predicts a larger increase in ApoA-I and a greater decrease in the pre-β1 level and fraction with ABCA1 up-regulation compared to CETP inhibition.

Conclusions The level of HDL-CE reflects the ratio of the RCT input rate to the clearance rate. Our in-silico model provides a tool for evaluating HDL-C raising targets in terms of their differential effects on the underlying metabolic processes.