Project Summary There were more than 2 million osteoporotic fractures in the U.S. in 2005, which exceeded the incidence of heart attack, stroke, and breast cancer combined. Osteoporotic fractures are associated with a high level of mortality and morbidity; more than one in five patients who suffer a hip fracture will die within one year due to causes related to their injury. The annual medical costs exceeded $17 billion in 2005 and are expected to increase to $25 billion by 2025. Bone physiology and adaptation are regulated by mechanical loading, which alters gene and protein expression in bone cells. Mechanical loads on bone are sensed by osteocytes embedded in the bone that signal to progenitor cells on the bone surface and in the marrow. Experiments have identified threshold levels of bone strain and cell shear stress that trigger osteocyte signaling, but are generally aggregated over many cells or larger regions of bone. These measures provide limited information about the stochastic or variable nature of cell responses to load. In the near future, computational power will allow models of bone adaptation incorporating response to individual cell signaling molecules to be employed to explore bone physiology and predict the response of bone to new treatments. Such models will provide better insight into experimental and clinical data related to bone diseases. In anticipation of these models, the goal of this project is to measure the probability of expression of key signaling genes in osteocytes based on the local mechanical environment. The aims are to measure gene expression in bone subsequent to controlled loading in a bioreactor system, calculate the stress field using high-fidelity computational models, and perform spatial correlations to determine the likelihood of altered gene expression for a given mechanical environment.