IADR Abstract Archives
Clinical Implants Differentially Modulate Inflammatory Response and Osteogenic Differentiation
Objectives: Surface modifications are applied to increase osseointegration of dental implants. Rough surfaces promote osteogenesis of mesenchymal stem cells (MSCs), and hydrophilic modifications induce anti-inflammatory macrophages activation. Effects of surface modifications on commercial dental implants have been compared in-vivo and clinically, focusing mainly on osseointegration and force-to-failure. However, the cellular response to commercially-available implants is overlooked. Our aim was to characterize the macrophage inflammatory response and MSC osteogenesis on commercially available implants in vitro.
Methods: Six commercially-available implants with the following surfaces [OsseoSpeed (Astra-Tech); Osseotite (Biomet-3i); TiUnit (Nobel-Biocare); SLA, RXD-SLA, RXD-SLActive (Straumann)] were examined. Primary murine macrophages and human MSCs were seeded directly on clinical implants and cultured in custom vials. Protein and mRNA levels of pro- (IL1B, IL6, IL17A, CXCL10, TNFa) and anti- (IL4, IL10, TGFB1) inflammatory markers and chemokines (Ccl2, Ccl3, Ccl4, Ccl5, Cxcl10) were measured after 24 and 48 hours in macrophages. Osteoblastic differentiation of MSCs was assessed after 7 days by alkaline phosphatase activity (ALP), osteocalcin, and angiogenic, osteogenic, and inflammatory markers by ELISA and qPCR (n=6/variable, ANOVA, post-hoc TUKEY HSD with α=0.05).
Results: Macrophages expressed the highest level of immune cell chemokines on TiUnit and Osseotite surfaces. These also elicited the greatest upregulation of pro-inflammatory factors and chemokines, and the lowest levels of anti-inflammatory factors. In contrast, RXD-SLActive had the highest anti-inflammatory and lowest pro-inflammatory factors. All surfaces increased ALP and osteocalcin, with the highest levels on RXD-SLActive and the lowest on TiUnit. RXD-SLActive had the highest osteoprotegerin and lowest RANKL, while the opposite was found for TiUnit.
Conclusions: We successfully evaluated commercially available clinical implants in-vitro. While all implants induced osteogenesis, the effect was greatest on RXD-SLActive. RXD-SLActive activated an anti-inflammatory macrophage phenotype, reducing pro-inflammatory cytokines. Our results demonstrate that in-vitro evaluation of clinical implants can be a powerful prediction model of clinical outcomes.
Methods: Six commercially-available implants with the following surfaces [OsseoSpeed (Astra-Tech); Osseotite (Biomet-3i); TiUnit (Nobel-Biocare); SLA, RXD-SLA, RXD-SLActive (Straumann)] were examined. Primary murine macrophages and human MSCs were seeded directly on clinical implants and cultured in custom vials. Protein and mRNA levels of pro- (IL1B, IL6, IL17A, CXCL10, TNFa) and anti- (IL4, IL10, TGFB1) inflammatory markers and chemokines (Ccl2, Ccl3, Ccl4, Ccl5, Cxcl10) were measured after 24 and 48 hours in macrophages. Osteoblastic differentiation of MSCs was assessed after 7 days by alkaline phosphatase activity (ALP), osteocalcin, and angiogenic, osteogenic, and inflammatory markers by ELISA and qPCR (n=6/variable, ANOVA, post-hoc TUKEY HSD with α=0.05).
Results: Macrophages expressed the highest level of immune cell chemokines on TiUnit and Osseotite surfaces. These also elicited the greatest upregulation of pro-inflammatory factors and chemokines, and the lowest levels of anti-inflammatory factors. In contrast, RXD-SLActive had the highest anti-inflammatory and lowest pro-inflammatory factors. All surfaces increased ALP and osteocalcin, with the highest levels on RXD-SLActive and the lowest on TiUnit. RXD-SLActive had the highest osteoprotegerin and lowest RANKL, while the opposite was found for TiUnit.
Conclusions: We successfully evaluated commercially available clinical implants in-vitro. While all implants induced osteogenesis, the effect was greatest on RXD-SLActive. RXD-SLActive activated an anti-inflammatory macrophage phenotype, reducing pro-inflammatory cytokines. Our results demonstrate that in-vitro evaluation of clinical implants can be a powerful prediction model of clinical outcomes.