A computational study of the dual effect of intermittent and continuous administration of parathyroid hormone on bone remodeling

Abstract

Bone remodeling is a process known to be governed by constant interactions between osteoblast and osteoclast through complex pathway networks mediated by signaling factors. Experimental studies show that intermittent and continuous administration of PTH/PTHrP led to opposite outcomes in terms of bone mass. To investigate this dual effect of PTH/PTHrP, we develop a computational model based on a simplified signaling pathway network which includes relevant molecular effectors and cells. Multiple ordinary differential equations linking all considered components in the signaling pathway network through reaction kinetics are solved with dose values and patterns of injection from experiments as input. Modeling results show good agreement with experimental observations in that continuous injection of PTH/PTHrP generates catabolic effect on bone mass while intermittent injection yields anabolic effect. The signaling factors governing the interaction between osteoblast and osteoclast indeed play a key role in the dual effect of PTH/PTHrP. Furthermore, there appears to be an optimal interval for intermittent injection of PTH/PTHrP for yielding the most bone regeneration, and a synergistic outcome could be achieved by combining intermittent injection of PTH/PTHrP with application of a treatment (to mimic the filling of bone defects with polymeric scaffolds). This modeling work sheds valuable insights into the influence of temporal control of PTH/PTHrP on bone mass and presents a possible path toward bridging bioengineering approaches with clinical treatment strategies. Statement of SignificanceA computational model considering simplified signaling pathways containing crucial components of PTH, PTHrP, osteoblast precursor, osteoblast, osteoclast precursor, osteoclast, RANKL and IL-6 family cytokoines has been developed to study the dual effect of PTH/PTHrP on bone metabolism. The model takes the dose values and patterns of injection from experiments as input and yields predictions that convincingly match experimental measurements. This work highlights the importance of providing an optimal hormone treatment strategy for maintaining healthy bone metabolism. Moreover, the integrative approach of relying on experimental observations to find reasonable values for relevant modeling parameters has been proven to be powerful in advancing our understanding of biological interactions among cells and signaling factors.