Salivary microbiota reflects changes in gut microbiota in cirrhosis with hepatic encephalopathy

Abstract

Altered gut microbiome is associated with systemic inflammation and cirrhosis decompensation. However, the correlation of the oral microbiome with inflammation in cirrhosis is unclear. Our aim was to evaluate the oral microbiome in cirrhosis and compare with stool microbiome. Outpatients with cirrhosis (with/without hepatic encephalopathy [HE]) and controls underwent stool/saliva microbiome analysis (for composition and function) and also systemic inflammatory evaluation. Ninety-day liver-related hospitalizations were recorded. Salivary inflammation was studied using T helper 1 cytokines/secretory immunoglobulin A (IgA), histatins and lysozyme in a subsequent group. A total of 102 patients with cirrhosis (43 previous HE) and 32 age-matched controls were included. On principal component analysis (PCA), stool and saliva microbiome clustered far apart, showing differences between sites as a whole. In salivary microbiome, with previous HE, relative abundance of autochthonous families decreased whereas potentially pathogenic ones (Enterobacteriaceae, Enterococcaceae) increased in saliva. Endotoxin-related predicted functions were significantly higher in cirrhotic saliva. In stool microbiome, relative autochthonous taxa abundance reduced in previous HE, along with increased Enterobacteriaceae and Enterococcaceae. Cirrhotic stool microbiota demonstrated a significantly higher correlation with systemic inflammation, compared to saliva microbiota, on correlation networks. Thirty-eight patients were hospitalized within 90 days. Their salivary dysbiosis was significantly worse and predicted this outcome independent of cirrhosis severity. Salivary inflammation was studied in an additional 86 age-matched subjects (43 controls/43 patients with cirrhosis); significantly higher interleukin (IL)-6/IL-1β, secretory IgA, and lower lysozyme, and histatins 1 and 5 were found in patients with cirrhosis, compared to controls.

Conclusions: Dysbiosis, represented by reduction in autochthonous bacteria, is present in both saliva and stool in patients with cirrhosis, compared to controls. Patients with cirrhosis have impaired salivary defenses and worse inflammation. Salivary dysbiosis was greater in patients with cirrhosis who developed 90-day hospitalizations. These findings could represent a global mucosal-immune interface change in cirrhosis.

Figure 1. Principal component analyses of microbiota change

Figure 1A: Salivary microbiota (black oval) cluster far apart from the stool in controls (squares=stool, circles=saliva) Figure 1B: Salivary microbiota (black oval) cluster far apart from the stool in cirrhosis (squares=stool, circles=saliva) Figure 1C: Stool microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE) Figure 1D: Salivary microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE)

Figure 1. Principal component analyses of microbiota change

Figure 1A: Salivary microbiota (black oval) cluster far apart from the stool in controls (squares=stool, circles=saliva) Figure 1B: Salivary microbiota (black oval) cluster far apart from the stool in cirrhosis (squares=stool, circles=saliva) Figure 1C: Stool microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE) Figure 1D: Salivary microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE)

Figure 1. Principal component analyses of microbiota change

Figure 1A: Salivary microbiota (black oval) cluster far apart from the stool in controls (squares=stool, circles=saliva) Figure 1B: Salivary microbiota (black oval) cluster far apart from the stool in cirrhosis (squares=stool, circles=saliva) Figure 1C: Stool microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE) Figure 1D: Salivary microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE)

Figure 1. Principal component analyses of microbiota change

Figure 1A: Salivary microbiota (black oval) cluster far apart from the stool in controls (squares=stool, circles=saliva) Figure 1B: Salivary microbiota (black oval) cluster far apart from the stool in cirrhosis (squares=stool, circles=saliva) Figure 1C: Stool microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE) Figure 1D: Salivary microbiota showing clustering of control and no-HE (black oval) compared to those with prior-HE that is not as apparent as between the control/cirrhosis comparisons (yellow circles=control, red circles=no-HE, red squares= prior-HE)

Figure 2. Predicted metabolic functions of microbiota in saliva and stool between groups

LDA score represents log changes in relative gene expression predicted function between groups. Bars in the green indicate higher activity in controls while those in red represent higher activity in cirrhotic saliva or stool. Figure 2A: Salivary predicted microbiota functional changes in controls is centered on amino-acid and phenolic metabolism while a higher expression of genes related to lipopolysaccharides and purine/pryrimidine metabolism was seen in cirrhotics’ saliva. Figure 2B: Stool predicted microbiota functional changes showing differences in cirrhotic and control microbiota. There was a higher expression of genes related to vitamins, cofactors and oxidant metabolism in cirrhosis while controls had a significantly higher expression of carbohydrate and amino-acid metabolism.

Figure 2. Predicted metabolic functions of microbiota in saliva and stool between groups

LDA score represents log changes in relative gene expression predicted function between groups. Bars in the green indicate higher activity in controls while those in red represent higher activity in cirrhotic saliva or stool. Figure 2A: Salivary predicted microbiota functional changes in controls is centered on amino-acid and phenolic metabolism while a higher expression of genes related to lipopolysaccharides and purine/pryrimidine metabolism was seen in cirrhotics’ saliva. Figure 2B: Stool predicted microbiota functional changes showing differences in cirrhotic and control microbiota. There was a higher expression of genes related to vitamins, cofactors and oxidant metabolism in cirrhosis while controls had a significantly higher expression of carbohydrate and amino-acid metabolism.

Figure 3. Correlation network differences

The following figures represent differences between correlations networks created for microbial families and inflammatory cytokines in saliva and stool. In all the subsequent figures, the light green nodes represent systemic inflammatory cytokines while red ones are microbial families. If the correlations are negative in both compared networks, the connecting line is red, if positive in both compared networks it is dark blue, if negative in one and turns to positive in the other, the line is dark green with arrows while if the correlations are positive in one and changes to negative in the other, the line is bright green with dashes. Figure 3A: Control saliva compared to Cirrhosis Saliva networks. The correlation network of salivary microbiota and inflammation and a similar network in cirrhotic saliva was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Between Incertae sedis XIV and Prevotellaceae, Negative/no correlation in control saliva but positive correlation in cirrhosis: inflammatory cytokines with each other, Positive/no correlation in control saliva but negative correlation in cirrhosis: Enterobacteriaceae with IL-10. This shows that cirrhosis saliva has more robust changes with systemic inflammation and within bacteria in the saliva compared to controls. Figure 3B: Control stool compared to Cirrhosis stool The correlation network of control stool microbiota and inflammation and a similar network in cirrhotic stool was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Enterobacteriaceae and Ruminococcaceae, Positive in both groups but more in cirrhosis: Incertae sedis XIV and Peptostreptococcaceae, Porphyromonadaceae with IL-13. Negative/no correlation in control stool but positive correlation in cirrhosis: inflammatory cytokines with each other, Incertae sedis XIV with Ruminococcaceae and Lachnospiraceae, Positive/no correlation in control stool but negative correlation in cirrhosis: Porphyromonadaceae with IL-10. The results demonstrate a higher correlation intensity in cirrhosis stool between autochthonous families and between non-autochthonous families and systemic inflammation. Figure 3C: Control stool compared to Control saliva The correlation network of control stool microbiota and inflammation and to control saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Negative in both control saliva and stool, but stronger negativity in saliva: Streptococcaceae with Ruminococcaceae and Lachnospiraceae Negative in both control saliva and stool but stronger negative correlation in stool: Enterobacteriaceae with Ruminococcaceae Negative in control stool without significant relationship/positive in control saliva: autochthonous taxa with Bacteroidaceae, Alcaligenaceae and with inflammatory cytokines Positive in control stool without significant relationship/negative in control saliva: Porphyromonadaceae and IL-10, Prevotellaceae and Incertae sedis XIV. These results show that the strength of most correlations between microbial families (positive or negative) is higher in stool compared to saliva even within the same control group. Figure 3D: Cirrhosis stool compared to Cirrhosis saliva The correlation network of cirrhosis stool microbiota and inflammation and to cirrhosis saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Positive in both cirrhosis saliva and stool but stronger positivity in saliva: Micrococcaceae and Streptococcaceae Positive in both cirrhosis saliva and stool but stronger positivity in stool: Enterococcaceae with IL-2, Autochthonous taxa with each other. Negative in both cirrhosis saliva and stool but stronger negative correlation in saliva: Lachnospiraceae with IL-2 Negative in cirrhosis stool without significant relationship/positive correlation in cirrhosis saliva: autochthonous taxa with Bacteroidaceae and with inflammatory cytokines, Positive in cirrhosis stool without significant relationship/negative correlation in saliva: Clostridiaceae with Peptostreptococcaceae. These results show that within the cirrhosis group, salivary correlations of autochthonous families and systemic inflammation and between predominant salivary microbes (Streptococaceae) were higher than in stool, while relationship with predominantly stool microbiota (Bacteroidaceae) with inflammation was higher in stool.

Figure 3. Correlation network differences

The following figures represent differences between correlations networks created for microbial families and inflammatory cytokines in saliva and stool. In all the subsequent figures, the light green nodes represent systemic inflammatory cytokines while red ones are microbial families. If the correlations are negative in both compared networks, the connecting line is red, if positive in both compared networks it is dark blue, if negative in one and turns to positive in the other, the line is dark green with arrows while if the correlations are positive in one and changes to negative in the other, the line is bright green with dashes. Figure 3A: Control saliva compared to Cirrhosis Saliva networks. The correlation network of salivary microbiota and inflammation and a similar network in cirrhotic saliva was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Between Incertae sedis XIV and Prevotellaceae, Negative/no correlation in control saliva but positive correlation in cirrhosis: inflammatory cytokines with each other, Positive/no correlation in control saliva but negative correlation in cirrhosis: Enterobacteriaceae with IL-10. This shows that cirrhosis saliva has more robust changes with systemic inflammation and within bacteria in the saliva compared to controls. Figure 3B: Control stool compared to Cirrhosis stool The correlation network of control stool microbiota and inflammation and a similar network in cirrhotic stool was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Enterobacteriaceae and Ruminococcaceae, Positive in both groups but more in cirrhosis: Incertae sedis XIV and Peptostreptococcaceae, Porphyromonadaceae with IL-13. Negative/no correlation in control stool but positive correlation in cirrhosis: inflammatory cytokines with each other, Incertae sedis XIV with Ruminococcaceae and Lachnospiraceae, Positive/no correlation in control stool but negative correlation in cirrhosis: Porphyromonadaceae with IL-10. The results demonstrate a higher correlation intensity in cirrhosis stool between autochthonous families and between non-autochthonous families and systemic inflammation. Figure 3C: Control stool compared to Control saliva The correlation network of control stool microbiota and inflammation and to control saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Negative in both control saliva and stool, but stronger negativity in saliva: Streptococcaceae with Ruminococcaceae and Lachnospiraceae Negative in both control saliva and stool but stronger negative correlation in stool: Enterobacteriaceae with Ruminococcaceae Negative in control stool without significant relationship/positive in control saliva: autochthonous taxa with Bacteroidaceae, Alcaligenaceae and with inflammatory cytokines Positive in control stool without significant relationship/negative in control saliva: Porphyromonadaceae and IL-10, Prevotellaceae and Incertae sedis XIV. These results show that the strength of most correlations between microbial families (positive or negative) is higher in stool compared to saliva even within the same control group. Figure 3D: Cirrhosis stool compared to Cirrhosis saliva The correlation network of cirrhosis stool microbiota and inflammation and to cirrhosis saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Positive in both cirrhosis saliva and stool but stronger positivity in saliva: Micrococcaceae and Streptococcaceae Positive in both cirrhosis saliva and stool but stronger positivity in stool: Enterococcaceae with IL-2, Autochthonous taxa with each other. Negative in both cirrhosis saliva and stool but stronger negative correlation in saliva: Lachnospiraceae with IL-2 Negative in cirrhosis stool without significant relationship/positive correlation in cirrhosis saliva: autochthonous taxa with Bacteroidaceae and with inflammatory cytokines, Positive in cirrhosis stool without significant relationship/negative correlation in saliva: Clostridiaceae with Peptostreptococcaceae. These results show that within the cirrhosis group, salivary correlations of autochthonous families and systemic inflammation and between predominant salivary microbes (Streptococaceae) were higher than in stool, while relationship with predominantly stool microbiota (Bacteroidaceae) with inflammation was higher in stool.

Figure 3. Correlation network differences

The following figures represent differences between correlations networks created for microbial families and inflammatory cytokines in saliva and stool. In all the subsequent figures, the light green nodes represent systemic inflammatory cytokines while red ones are microbial families. If the correlations are negative in both compared networks, the connecting line is red, if positive in both compared networks it is dark blue, if negative in one and turns to positive in the other, the line is dark green with arrows while if the correlations are positive in one and changes to negative in the other, the line is bright green with dashes. Figure 3A: Control saliva compared to Cirrhosis Saliva networks. The correlation network of salivary microbiota and inflammation and a similar network in cirrhotic saliva was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Between Incertae sedis XIV and Prevotellaceae, Negative/no correlation in control saliva but positive correlation in cirrhosis: inflammatory cytokines with each other, Positive/no correlation in control saliva but negative correlation in cirrhosis: Enterobacteriaceae with IL-10. This shows that cirrhosis saliva has more robust changes with systemic inflammation and within bacteria in the saliva compared to controls. Figure 3B: Control stool compared to Cirrhosis stool The correlation network of control stool microbiota and inflammation and a similar network in cirrhotic stool was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Enterobacteriaceae and Ruminococcaceae, Positive in both groups but more in cirrhosis: Incertae sedis XIV and Peptostreptococcaceae, Porphyromonadaceae with IL-13. Negative/no correlation in control stool but positive correlation in cirrhosis: inflammatory cytokines with each other, Incertae sedis XIV with Ruminococcaceae and Lachnospiraceae, Positive/no correlation in control stool but negative correlation in cirrhosis: Porphyromonadaceae with IL-10. The results demonstrate a higher correlation intensity in cirrhosis stool between autochthonous families and between non-autochthonous families and systemic inflammation. Figure 3C: Control stool compared to Control saliva The correlation network of control stool microbiota and inflammation and to control saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Negative in both control saliva and stool, but stronger negativity in saliva: Streptococcaceae with Ruminococcaceae and Lachnospiraceae Negative in both control saliva and stool but stronger negative correlation in stool: Enterobacteriaceae with Ruminococcaceae Negative in control stool without significant relationship/positive in control saliva: autochthonous taxa with Bacteroidaceae, Alcaligenaceae and with inflammatory cytokines Positive in control stool without significant relationship/negative in control saliva: Porphyromonadaceae and IL-10, Prevotellaceae and Incertae sedis XIV. These results show that the strength of most correlations between microbial families (positive or negative) is higher in stool compared to saliva even within the same control group. Figure 3D: Cirrhosis stool compared to Cirrhosis saliva The correlation network of cirrhosis stool microbiota and inflammation and to cirrhosis saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Positive in both cirrhosis saliva and stool but stronger positivity in saliva: Micrococcaceae and Streptococcaceae Positive in both cirrhosis saliva and stool but stronger positivity in stool: Enterococcaceae with IL-2, Autochthonous taxa with each other. Negative in both cirrhosis saliva and stool but stronger negative correlation in saliva: Lachnospiraceae with IL-2 Negative in cirrhosis stool without significant relationship/positive correlation in cirrhosis saliva: autochthonous taxa with Bacteroidaceae and with inflammatory cytokines, Positive in cirrhosis stool without significant relationship/negative correlation in saliva: Clostridiaceae with Peptostreptococcaceae. These results show that within the cirrhosis group, salivary correlations of autochthonous families and systemic inflammation and between predominant salivary microbes (Streptococaceae) were higher than in stool, while relationship with predominantly stool microbiota (Bacteroidaceae) with inflammation was higher in stool.

Figure 3. Correlation network differences

The following figures represent differences between correlations networks created for microbial families and inflammatory cytokines in saliva and stool. In all the subsequent figures, the light green nodes represent systemic inflammatory cytokines while red ones are microbial families. If the correlations are negative in both compared networks, the connecting line is red, if positive in both compared networks it is dark blue, if negative in one and turns to positive in the other, the line is dark green with arrows while if the correlations are positive in one and changes to negative in the other, the line is bright green with dashes. Figure 3A: Control saliva compared to Cirrhosis Saliva networks. The correlation network of salivary microbiota and inflammation and a similar network in cirrhotic saliva was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Between Incertae sedis XIV and Prevotellaceae, Negative/no correlation in control saliva but positive correlation in cirrhosis: inflammatory cytokines with each other, Positive/no correlation in control saliva but negative correlation in cirrhosis: Enterobacteriaceae with IL-10. This shows that cirrhosis saliva has more robust changes with systemic inflammation and within bacteria in the saliva compared to controls. Figure 3B: Control stool compared to Cirrhosis stool The correlation network of control stool microbiota and inflammation and a similar network in cirrhotic stool was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were different are shown and explained below. Negative correlations in cirrhosis and controls both but more significant in cirrhosis: Enterobacteriaceae and Ruminococcaceae, Positive in both groups but more in cirrhosis: Incertae sedis XIV and Peptostreptococcaceae, Porphyromonadaceae with IL-13. Negative/no correlation in control stool but positive correlation in cirrhosis: inflammatory cytokines with each other, Incertae sedis XIV with Ruminococcaceae and Lachnospiraceae, Positive/no correlation in control stool but negative correlation in cirrhosis: Porphyromonadaceae with IL-10. The results demonstrate a higher correlation intensity in cirrhosis stool between autochthonous families and between non-autochthonous families and systemic inflammation. Figure 3C: Control stool compared to Control saliva The correlation network of control stool microbiota and inflammation and to control saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Negative in both control saliva and stool, but stronger negativity in saliva: Streptococcaceae with Ruminococcaceae and Lachnospiraceae Negative in both control saliva and stool but stronger negative correlation in stool: Enterobacteriaceae with Ruminococcaceae Negative in control stool without significant relationship/positive in control saliva: autochthonous taxa with Bacteroidaceae, Alcaligenaceae and with inflammatory cytokines Positive in control stool without significant relationship/negative in control saliva: Porphyromonadaceae and IL-10, Prevotellaceae and Incertae sedis XIV. These results show that the strength of most correlations between microbial families (positive or negative) is higher in stool compared to saliva even within the same control group. Figure 3D: Cirrhosis stool compared to Cirrhosis saliva The correlation network of cirrhosis stool microbiota and inflammation and to cirrhosis saliva microbiota and inflammation was compared to evaluate differences that were p<0.001 and r>0.6 or <−0.6. Relationships between microbiota and inflammatory markers that were changed significantly are shown and explained below. Positive in both cirrhosis saliva and stool but stronger positivity in saliva: Micrococcaceae and Streptococcaceae Positive in both cirrhosis saliva and stool but stronger positivity in stool: Enterococcaceae with IL-2, Autochthonous taxa with each other. Negative in both cirrhosis saliva and stool but stronger negative correlation in saliva: Lachnospiraceae with IL-2 Negative in cirrhosis stool without significant relationship/positive correlation in cirrhosis saliva: autochthonous taxa with Bacteroidaceae and with inflammatory cytokines, Positive in cirrhosis stool without significant relationship/negative correlation in saliva: Clostridiaceae with Peptostreptococcaceae. These results show that within the cirrhosis group, salivary correlations of autochthonous families and systemic inflammation and between predominant salivary microbes (Streptococaceae) were higher than in stool, while relationship with predominantly stool microbiota (Bacteroidaceae) with inflammation was higher in stool.