Can Genetic Factors Compromise the Success of Dental Implants? A Systematic Review and Meta-Analysis

Abstract

Dental implants provide a predictable treatment option for partial and complete edentulism via the placement of a fixed permanent artificial root to support prosthetic dental crowns. Despite the high survival rates, long-term dental implant failures are still reported, leading to implant removals and additional financial and health burdens. While extrinsic factors that improve the success rate of implants have been well explored, the impact of genetic factors on this matter is poorly understood. A systematic review and meta-analysis study was conducted to determine whether genetic factors contribute to an increased risk of dental implant failures. A comprehensive search for peer-reviewed articles on dental implants and genetic factors was performed using various literature database libraries. The study design was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, and the obtained records were registered in the International Prospective Register of Systematic Reviews (PROSPERO) database. According to the exclusion/inclusion criteria, 13 studies were eligible for this study out of 809 articles. The meta-analysis of the combined association studies of DNA variations and dental implants did not indicate an increased risk for implant failure due to DNA variations in IL-1B, IL-10 and TNF-α. This study emphasizes the need for larger randomized controlled clinical trials to inform clinicians and patients about the role of genetic factors on dental implant survival and the success rate in healthy and compromised patients.

Keywords: bone quality; bone regeneration; dental implants; genetic factors; survival rate.

Figure 1

A flowchart representing the literature search, screening, eligibility and selection of this study.

Figure 2

Odds ratio (OR) and forest plot for the prevalence of IL1B-C511 allele in the failure group (at least one implant failure) vs. control group (without implant failure). The OR of the combined data crossed the line of no difference.

Figure 3

Odds ratio and forest plot for the prevalence of the IL1B-T511 allele in the failure group (at least one implant failure) vs. control group (without implant failure). The OR of the combined data crossed the line of no difference.

Figure 4

Odds ratio and forest plot for the prevalence of IL10-G1082 allele in the failure group (at least one implant failure) vs. control group (without implant failure). The OR of the combined data crossed the line of no difference.

Figure 5

Odds ratio and forest plot for the prevalence of IL10-A1082 allele in the failure group (at least one implant failure) vs. control group (without implant failure). The OR of the combined data crossed the line of no difference.

Figure 6

Odds ratio and forest plot for the prevalence of TNF-α-A308 allele in the failure group (at least one implant failure) vs. control group (without implant failure). The OR of the combined data crossed the line of no difference.

Figure 7

Odds ratio and forest plot for the prevalence of TNF-α-G308 allele in the failure group (at least one implant failure) vs. control group (without implant failure). The OR of the combined data crossed the line of no difference.

Figure 8

A funnel graph for the homogeneity representation of the meta-analysis. The data shows that the plotted homogeneity is acceptable for the DNA alleles used in the meta-analysis, including the IL1B-C allele study group (A), IL1B-T allele (B), IL10-G allele (C), IL10-A allele (D), TNFα-A allele (E), and TNFα-G allele (F). SE (log[OR]) = standard error of the natural logarithm of the odds ratio.