Human variation in gingival inflammation

Shatha Bamashmous, Georgios A Kotsakis, Kristopher A Kerns, Brian G Leroux, Camille Zenobia, Dandan Chen, Harsh M Trivedi, Jeffrey S McLean, Richard P Darveau, Shatha Bamashmous, Georgios A Kotsakis, Kristopher A Kerns, Brian G Leroux, Camille Zenobia, Dandan Chen, Harsh M Trivedi, Jeffrey S McLean, Richard P Darveau

Abstract

Oral commensal bacteria actively participate with gingival tissue to maintain healthy neutrophil surveillance and normal tissue and bone turnover processes. Disruption of this homeostatic host-bacteria relationship occurs during experimental gingivitis studies where it has been clearly established that increases in the bacterial burden increase gingival inflammation. Here, we show that experimental gingivitis resulted in three unique clinical inflammatory phenotypes (high, low, and slow) and reveal that interleukin-1β, a reported major gingivitis-associated inflammatory mediator, was not associated with clinical gingival inflammation in the slow response group. In addition, significantly higher levels of Streptococcus spp. were also unique to this group. The low clinical response group was characterized by low concentrations of host mediators, despite similar bacterial accumulation and compositional characteristics as the high clinical response group. Neutrophil and bone activation modulators were down-regulated in all response groups, revealing novel tissue and bone protective responses during gingival inflammation. These alterations in chemokine and microbial composition responses during experimental gingivitis reveal a previously uncharacterized variation in the human host response to a disruption in gingival homeostasis. Understanding this human variation in gingival inflammation may facilitate the identification of periodontitis-susceptible individuals. Overall, this study underscores the variability in host responses in the human population arising from variations in host immune profiles (low responders) and microbial community maturation (slow responders) that may impact clinical outcomes in terms of destructive inflammation.

Keywords: chemokine; gingivitis; inflammation; oral microbiome; periodontitis.

Conflict of interest statement

Competing interest statement: This work was funded in part by a Colgate-Palmolive clinical research grant (R.P.D., PI). This funding source had no role in the design of this study and did not have any role during its implementation, analyses, interpretation of the data, or decision to submit results.

Copyright © 2021 the Author(s). Published by PNAS.

Figures

Fig. 1.
Fig. 1.
Experimental gingivitis study design. (A) Experimental cessation of oral hygiene leads to increased plaque biomass and induced gingivitis. Within-subject contralateral teeth with regular oral hygiene served as controls. Baseline was established from day −14 to day 0. Induction of experimental gingival inflammation was carried out from day 0 through day 21. Resolution of experimental gingivitis was observed from day 21 until day 35 when no residual clinical inflammatory activity was detectable (see SI Appendix, Supplemental Materials and Methods). Comprehensive clinical, chemokine and microbiome analysis were conducted to obtain highly granular multiplexed analyses of changes during induction and resolution of inflammation. (B) Percentages of subjects that were clustered into the three clinical response groups (high, low, and slow) based on longitudinal trajectories of clinical parameters (GI, PI, and BOP) (SI Appendix, Fig. S1).
Fig. 2.
Fig. 2.
Differential clinical inflammatory responses and chemokine levels in the three response groups versus controls. (A–D) Distributions of clinical parameters comparing test side (no-brushing) versus control side (brushed) for all subjects over time. (E–H) Temporal changes in inflammatory-associated clinical measures stratified by response group (high [n = 6], low [n = 6], slow [n = 9]). (I–L) Responses among sample-sites in each of three clinical inflammatory response groups (high, low, and slow) before, during, and after resolution of bacterial-induced inflammation. (I) Bacterial load based on total 16S rRNA gene copies; y axis log10-scaled. (J) Neutrophil marker MPO. (K and L) proinflammatory cytokine IL-1β. Boxes represent data and medians ± interquartile ranges (IQR); whiskers and outliers > 1.5 IQR below (above) the 25th (75th) percentile. Trend lines represent mean values across time points. Different letters above bars indicate the significant differences between groups at that time point (a, b, c) (FDR P < 0.05). In A–D statistical analyses were performed against the controls by comparing all test samples (prior to responder group identification) and all pooled data from the control teeth data (intraoral control) for just these select clinical parameters and only calculated for the induction phase. In E–L the responder groups are shown in relation to the pooled control group. Control samples were never physically pooled; however, the data, for clarity in the figures, was reduced from the total six groups (three test and three control) to four groups (three test and one pooled control). Differences of each group compared to baseline (day 0) are shown above the groups and their significance level indicated by asterisks. Significance levels: *P < 0.05, **P ≤ 0.01, and ***P ≤ 0.001. (L) Comparison of IL-1β levels between groups at peak clinical inflammatory endpoint (day 21) show the subjects in the slow group were significantly different from the high responder group that displayed elevated IL-1β.
Fig. 3.
Fig. 3.
Relationship between chemokine levels and the three clinical response groups. (A) Normalized (row-wise z-score) mean values for chemokine expression by responder groups and controls (all responder groups’ control side data are combined for clarity) by day. The low responder group displays several SDs below the mean of all the groups in most chemokines. (B) Temporal relationships between major neutrophil chemokines IL-8/CXCL8 and MIF with MPO and bacterial load. MIF demonstrated an inverted U-shape distribution during the induction-resolution human experiment that was similar to the temporal changes in microbial load (negative quadratic coefficients; P < 0.01 for both MIF and bacterial load). MPO changes followed the same temporal pattern as MIF (negative quadratic coefficient; P < 0.001), while IL-8/CXCL8 levels demonstrated a U-shape distribution with no association to MPO levels (positive quadratic coefficient; P = 0.09). (C–H) Temporal changes in major neutrophil chemokines (MIF, IL-8/CXCL8, and GCP-2/CXCL6) across responder groups compared to each of the responder groups (C, E, G) and between their respective control side sample in the split-mouth design (D, F, H). Boxes represents data and medians ± IQR; whiskers and outliers > 1.5 IQR below (above) the 25th (75th) percentile. Trend lines represent mean values across time points. For D, F, and H, separate controls for each group in were displayed against their respective healthy controls. Differences of each group compared to baseline (day 0) are shown above the groups and their significance level indicated by asterisks. Significance levels: *P < 0.05 and **P ≤ 0.01.
Fig. 4.
Fig. 4.
(A–F) Changes in levels of chemokines involved in bone homeostasis following induction of reversible bone-sparing gingival inflammation. Responses among sample-sites in each of three clinical inflammatory response groups before, during, and after resolution of bacterial-induced inflammation. Boxes represents data and medians ± IQR; whiskers and outliers > 1.5 IQR. Trend lines represent mean values across time points. Different letters above bars indicate the significant differences between groups at that time point (a, b, c) (FDR P < 0.05). Differences of each group compared to baseline (day 0) are shown above the groups and their significance level indicated by asterisks. Significance levels: *P < 0.05, **P ≤ 0.01, and ***P ≤ 0.001.
Fig. 5.
Fig. 5.
Temporal changes in microbial diversity and taxonomy vary by inflammatory responder type. (A) Faith’s phylogenetic diversity by responder group and controls from day −14 to day 35 (n = 334 samples from 21 subjects). Boxplots show median and 25th/75th quartiles; whiskers show inner fences. Lines show mean richness by clinical responder group (high, low, and slow) and controls (within-subject noninflamed gingival sites). (B) Nonmetric multidimensional scaling (NMDS) plots of β-diversity (unweighted Unifrac distance matrices) by responder group and controls from day −14 to day 35 (n = 334 samples from 21 subjects). Tests for significance in β-diversity between groups determined by PERMANOVA. (C) Phylum-level distributions of relative abundance by responder group and controls from day −14 to day 35 (n = 334 samples from 21 subjects). (D and E) Genus-level mean relative abundance by responder group and controls from day −14 to day 35. Linear regression (Loess) shown with 95% confidence bound (SI Appendix, Supplemental Materials and Methods) (n = 334 samples from 21 subjects). (F) Streptococcus mean relative abundance by responder group and controls from day −14 to day 35 (n = 334 samples from 21 subjects). Also shown are center log-transformed (CLR) relative abundances of ASVs taxonomically assigned to S. sanguinis and S. oralis species in high, slow, and low inflammatory response groups from day −14 and day 35. Boxplots show median and lower/upper quartiles; whiskers show inner fences (Materials and Methods) (n = 84 from 21 subjects), (Wilcoxon test; adjusted by FDR) (SI Appendix, Supplemental Materials and Methods and Table S5). Asterisks show FDR-corrected statistical significance levels (FDR **P ≤ 0.01 and ****P ≤ 0.0001).

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