The Influence of Bone Type on the Gene Expression in Normal Bone and at the Bone‐Implant Interface: Experiments in Animal Model

Abstract

Studies on the biological processes in different bone types and the reaction of different bone types to biomaterials are often hindered because of the difficulties in sampling procedures and lack of sensitive techniques. The purpose was to assess the suitability of quantitative polymerase chain reaction (qPCR) for investigation of the biological differences between cortical and trabecular bone types and their responses to biomaterials. Gene expression of selected markers in rat bone samples from different locations was evaluated. Samples were harvested by trephines from the trabecular femoral epiphysis, cortico-trabecular proximal tibial metaphysic, and the cortical distal tibial metaphysis. Gene expression was also evaluated at the surfaces of anodically oxidized implants retrieved from cortical and trabecular sites after 3 days of implantation. mRNA in the bone samples and in the tissue associated with the implant surfaces was extracted and quantified using qPCR. Tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), alkaline phosphatase (ALP), osteocalcin (OC), tartrate-resistant acid phosphatase (TRAP), cathepsin K (CATK), and 18S ribosomal subunits (18S) were analyzed. In the bone samples, higher expression of ALP, OC, TRAP, and CATK was found in femoral epiphysis compared to proximal or distal tibial metaphysis, indicating a higher turnover in the trabecular bone. On the other hand, TNF-α and IL-1β showed higher expression in both tibia sites compared with the femur site, which suggests higher inflammatory potential in the cortical bone. In response to the oxidized implants trabecular bone expressed a higher level of IL-1β, whereas the implants in cortical bone were associated with higher expression of ALP and OC. There are biological differences between cortical and trabecular bone types, both in the normal steady-state condition and in response to biomaterials. Such differences can be characterized and discriminated quantitatively using a sensitive technique such as qPCR.