Association of 41 Inflammatory Cytokines With Common Oral Diseases

Abstract

Background: While observational studies have demonstrated a potential link between inflammatory cytokines and oral diseases, the question of causality is warranting further investigation. This study aimed to comprehensively assess the potential causal role of 41 inflammatory cytokines in common oral diseases.

Methods: A two-sample Mendelian randomization (MR) study was conducted using the summary statistics from the largest publicly available genome-wide association study (GWAS) for 41 inflammatory cytokines and common oral diseases (indicated by the index of decayed and filled tooth surfaces divided by number of tooth surfaces (DFSS), index of decayed, missing and filled tooth surfaces (DMFS), number of natural teeth, and periodontitis). Inverse variance weighted regression (IVW) was used as the primary method to estimate odds ratios (OR) and 95% confidence interval (CI) for assessing the causal effect. Sensitivity analyses with other four analytical approaches were performed to test the validity of our findings.

Results: Increased levels of hepatocyte growth factor (HGF) and stem cell growth factor beta (SCGF-β) were significantly associated with the risk of DFSS, with the ORs of 1.058 (95% CI: 1.004-1.115, P = .033) and 1.035 (95% CI:1.002-1.069, P = .038), respectively. Interleukin-1 receptor antagonist (IL-1RA) exhibited a negative association with DMFS (OR = 0.934, 95% CI: 0.886-0.985, P = .012). Furthermore, interleukin-9 (IL-9) was associated with in increased risk of periodontitis (OR = 1.148, 95% CI:1.031-1.277, P = .011). Additionally, no significant association was found between inflammatory cytokines and the number of natural teeth. Sensitivity analyses yielded generally consistent results.

Conclusions: This MR study provides evidence supporting potential causal associations of four inflammatory cytokines (HGF, SCGF-β, IL-1RA, IL-9) with the risk of common oral diseases, which may contribute to the development of more targeted prevention strategies for these diseases.

Keywords: Dental caries; Inflammatory cytokines; Mendelian randomization; Oral diseases; Periodontitis.

Fig. 1

Flow chart of the methodology in this study, including the selection of inflammatory cytokines, common oral diseases, and statistical techniques applied for Mendelian randomization analysis. The common oral diseases were indicated by the index of decayed and filled tooth surfaces divided by number of tooth surfaces (DFSS), index of decayed, missing and filled tooth surfaces (DMFS), number of natural teeth, and periodontitis).

Fig. 2

Forest plot results for analyzing potential causal relationships between inflammatory cytokines and dental caries using DFSS and DMFS indicators. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using the inverse variance weighted method. Each point represents an estimate of the effect size, with horizontal lines indicating 95% CI. Significant P values (P < .05) are bolded. Abbreviations: SNP, single-nucleotide polymorphism; DFSS, decayed and filled tooth surfaces divided by number of tooth surfaces; DMFS, decayed, missing and filled tooth surfaces.

Fig. 3

Bubble plots of potential associations of inflammatory cytokines with three outcomes using the IVW method. A, For DFSS (index of decayed and filled tooth surfaces divided by number of tooth surfaces); B, For DMFS (index of decayed, missing and filled tooth surfaces); C, For periodontitis. The y-axis represents the −log10 (P value) effect for the association, while the x-axis illustrates the corresponds log (odds ratio) effect for each cytokine on three distinct outcomes. A red bubble signifies a P value of less than .05, whereas a blue bubble denotes a P value greater than or equal to .05.

Fig. 4

Forest plot results for analyzing potential causal relationships between inflammatory cytokines and dental caries using periodontitis and the number of natural teeth indicators. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using the inverse variance weighted method. Each point represents an estimate of the effect size, with horizontal lines indicating 95% CI. Significant P values (P < .05) are bolded. Abbreviations: SNP, single-nucleotide polymorphism.

Fig. 5

Scatter plots showing causality estimates for IL-9, HGF, SCGF-β and IL-1RA using five methods (IVW, MR-Egger, Weighted-median, Simple mode, and Weighted mode). Scatter diagrams illustrate the per-allele correlation with the risk of outcome (y-axis) versus the per-allele correlation with one standard deviation of exposure (x-axis), with grey vertical and horizontal lines indicating the 95% confidence intervals for each SNP. Each dot represents one of the SNPs used in the genetic instrument variables. The slope of each line corresponds to the estimated MR effect of each method. Abbreviations: SNP, single-nucleotide polymorphism; DFSS, decayed and filled tooth surfaces divided by number of tooth surfaces; DMFS, decayed, missing and filled tooth surfaces.