Immune-Metabolic Regulation of Early Osseointegration: Insights from Untargeted RNA Sequencing

This study clarified how implant surfaces influence early osseointegration by coupling untargeted RNA sequencing with histomorphometry. Four rabbits each received three tibial implants: turned commercially pure titanium (Ti), sandblasted/large-grit/acid-etched titanium (SLA-Ti), and turned copper (Cu). Surface morphology was characterized by scanning electron microscopy, confocal microscopy, and energy dispersive spectroscopy. After 10 days, bone-to-implant contact (BIC), bone area (BA), and peri-implant transcriptomes were analyzed. Differentially expressed genes and Gene ontology (GO) enrichment were computed. SLA-Ti showed the greatest roughness. Both Ti groups yielded significantly higher BIC and BA than Cu (p < 0.001). GO terms on SLA-Ti were enriched for immune regulation and turned Cu was dominated by mitochondrial-stress pathways. Turned Ti showed minimal enrichment. SLA-Ti simultaneously up-regulated pro-inflammatory cytokines and immunoregulatory genes plus stress-adaptive markers, suggesting a balanced inflammatory milieu conducive to bone formation. Turned Cu markedly elevated mitochondrial genes and oxidative-stress markers, while suppressing antioxidant and innate-defense genes, reflecting immune-metabolic dysregulation. Turned Ti induced only modest transcript changes, consistent with passive biocompatibility. Early osseointegration hinges on a finely tuned immune-metabolic equilibrium rather than surface roughness alone. Optimal integration demands implant surfaces that trigger controlled immunomodulation while limiting oxidative stress, guiding the design of next-generation dental implants. Four rabbits each received three tibial implants: turned commercially pure titanium (Ti), sandblasted/large-grit/acid-etched titanium (SLA-Ti), and turned copper (Cu). Surface morphology was characterized by scanning electron microscopy, confocal microscopy, and energy dispersive spectroscopy. After 10 days, bone-to-implant contact (BIC), bone area (BA), and peri-implant transcriptomes were analyzed. Differentially expressed genes and Gene ontology (GO) enrichment were computed.