Specific gene expression patterns associated as reliable biomarkers for predicting dental implant successful osseointegration: a literature review and focused meta-analysis

TL;DR

This paper reviews how gene expression patterns can predict the success of dental implants by analyzing molecular and genetic signals involved in osseointegration.

Contribution

The study identifies specific genes and expression patterns as potential biomarkers for successful dental implant integration.

Findings

Successful osseointegration is marked by increased expression of bone-regulating genes like RUNX2 and production of bone matrix proteins.

Implant failure is associated with elevated inflammatory markers (IL-1β, IL-6, TNF-α) and an imbalanced RANKL/OPG ratio.

Modified implant surfaces significantly upregulate RUNX2 expression, promoting osteogenic activity.

Abstract

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. Furthermore, a quantitative meta-analysis was performed on a subset of homogenous in vitro studies.

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 actively guide these genetic pathways and shape the resulting cellular behavior. The findings revealed 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.

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