Microbial profiles at baseline and not the use of antibiotics determine the clinical outcome of the treatment of chronic periodontitis

Abstract

Antibiotics are often used in the treatment of chronic periodontitis, which is a major cause of tooth loss. However, evidence in favour of a microbial indication for the prescription of antibiotics is lacking, which may increase the risk of the possible indiscriminate use of antibiotics, and consequent, microbial resistance. Here, using an open-ended technique, we report the changes in the subgingival microbiome up to one year post-treatment of patients treated with basic periodontal therapy with or without antibiotics. Antibiotics resulted in a greater influence on the microbiome 3 months after therapy, but this difference disappeared at 6 months. Greater microbial diversity, specific taxa and certain microbial co-occurrences at baseline and not the use of antibiotics predicted better clinical treatment outcomes. Our results demonstrate the predictive value of specific subgingival bacterial profiles for the decision to prescribe antibiotics in the treatment of periodontitis, but they also indicate the need for alternative therapies based on ecological approaches.

Figure 1. Relative abundances of the major genera or higher taxa.

(a) Taxa that were significantly reduced by both treatments; (b) taxa that increased after the treatments; (c) taxa that were affected only in the Test group and (d) that were minimally affected by any of the treatments, for each time point (BL – baseline, 3M – 3 months, 6M – 6 months, 12M – 12 months) and treatment (Test or Control). *Statistically significant difference between the treatment groups (P < 0.05; Mann-Whitney test). Connectors connect the time-points within the same group in which the taxa proportions differed significantly (P < 0.05, Wilcoxon Signed Ranks test).

Figure 2. Principal component analysis (PCA) plots.

Plots represent the samples in the Control group (a) and the Test group (b), coloured by time-point (each colour indicates a different time-point). In panels (c–f) plots represent the individual samples for each separate time-point. White squares represent individuals in the control group, black squares represent individuals in the test group (F and P values were obtained with PERMANOVA test).

Figure 3. Average Bray-Curtis similarity of microbiome profiles.

Bars represent differences between the baseline visit (BL) and the other visits (3M – 3 months, 6M – 6 months, 12M – 12 months after therapy) for each individual according to treatment group (Test and Control). Connector indicates statistically significant difference between the groups (P < 0.001, independent samples T-test).

Figure 4. Correlation between Shannon diversity index at baseline and per cent change of Clinical Attachment Level (% CAL change) of the sampled sites at 12 months.

Light coloured dots represent patients in the test group and dark coloured dots represent patients in the control group. The vertical line represents the cut-off point (24.08%) between Below Median Responders (BMRs) and Above Median Responders (AMRs).

Figure 5. Average Shannon Diversity Index according to treatment modality and treatment outcome.

(a) Below Median Responders (BMRs) and Above Median Responders (AMRs) in the Control group and (b) the Test group samples per time point (BL – baseline, 3M – 3 months, 6M – 6 months, 12M – 12 months). The error bars indicate standard deviation. The connector indicates a statistically significant difference (P < 0.05, Independent samples T-test).

Figure 6. Average Bray-Curtis similarity in microbiome profiles according to treatment modality and treatment outcome.

Bars represent differences between the baseline visit (BL) and the other visits (3M – 3 months, 6M – 6 months, 12M – 12 months since the treatment) of each individual by clinical response at one-year follow-up (a) in the Test group and (b) in the Control group. Test: N = 9 Above Median Responders (AMRs), N = 9 Below Median Responders (BMRs); Control group: N = 10 Above Median Responders (AMRs), N = 9 Below Median Responders (BMRs). Error bars indicate standard deviations. Connector indicates a statistically significant difference between the groups (independent samples T-test).

Figure 7. Microbial co-occurrence or mutual exclusion networks between genera.

(a) Baseline taxonomic networks for the below median responders (BMRs) and (b) the above median responders (AMRs). (c) 12-month follow-up taxonomic network for below the median responders (BMRs) and (d) the above median responders (AMRs). Only edges that were significant by at least two of the methods (i.e. Pearson and Spearman correlations, Bray-Curtis similarity and Kullback-Leibler divergence) after correction for multiple comparisons were included in the network. The grey edges indicate positive correlations, and the negative correlations are indicated in red (P < 0.05). The size of the node is indicative of the relative abundance of the respective taxon. The colour of the node indicates the number of connections in the range of red to green; red indicates one connection, while green indicates >3 connections.