Specific gene expression patterns associated as reliable biomarkers for predicting dental implant successful osseointegration: A Literature Review and Focused Meta-analysis

Jesus Alejandro Serrato-Pedrosa^1*Virgilio Bocanegra-García²Ignacio Villanueva-Fierro¹Absalom Zamorano-Carrillo³Erwing Irving Rendón-Ramírez⁴Verónica Loera-Castañeda^1*

• ¹Academy of Genomics, Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional Unidad Durango, Instituto Politécnico Nacional (IPN), Durango, Mexico
• ²Centro de Biotecnología Genómica, Instituto Politécnico Nacional. Boulevard del Maestro S/N Esq. Elías Piña, Colonia Narciso Mendoza. Reynosa, 88710, Tamaulipas, C.P, Mexico., Reynosa, Mexico
• ³Laboratorio de Biofísica Computacional, Doctorado en Biotecnología, SEPI-ENMH Instituto Politécnico Nacional, 07320, Ciudad de México, Mexico., Mexico City, Mexico
• ⁴Vivental. Grupo Odontológico. Calle Laureano Roncal Norte No. 216, Col. Victoria de Durango Centro, Durango C.P. 34000, Mexico., Durango, Mexico

Scientific understanding of dental implant success has evolved significantly. Nowadays, it is well established that the long-term stability of an implant relies on osseointegration, a complex biological process directed by molecular and genetic signals at the bone-implant interface. This systematic review research synthesizes the recent scientific literature to identify specific genes and expression patterns that can indicate implant outcomes. Hence, the systematic review examines key signaling pathways, the influence of implant surface characteristics on cellular responses, and the potential for patient-specific therapeutic strategies. For this synthesis, relevant studies published between January 2020 and May 2025 were identified using the MEDLINE (via PubMed), Scopus and Web of Science databases, along the PRISMA methodology was employed. The collected evidence reveals a distinct molecular signature for successful integration, initiated by the increased expression of primary bone-regulating genes, such as RUNX2 and followed by the production of essential bone matrix proteins. In contrast, implant failure and peri-implantitis show a consistent association with a malfunctioning inflammatory response. This state is marked by elevated concentrations of inflammatory messengers (IL-1β, IL-6, and TNF-α) and an imbalanced RANKL/OPG ratio that favors bone resorption. Crucially, the implant surface is not a passive component in this process, its micro and nanoscale features are shown to This is a provisional file, not the final typeset article actively guide these genetic pathways and shape the resulting cellular behavior. Furthermore, a quantitative meta-analysis was performed on a subset of homogenous in vitro studies, revealing that modified implant surfaces significantly upregulate the expression of the key osteogenic transcription factor RUNX2 (Standardized Mean Difference: 2.58; 95% CI: 1.21 to 3.95; p < 0.001). The central conclusion is that specific, measurable gene expression patterns show promise as potential indicators of the biological processes governing dental implant outcomes. The emerging paradigm of implantogenomics aims to enable clinicians to perform personalized risk assessments and utilize advanced implant technologies to design individual, unique biological profile therapies and strategies, thereby optimizing the potential for long-term clinical success.