Evidence for a distinct gut microbiome in kidney stone formers compared to non-stone formers

Abstract

The trillions of microbes that colonize our adult intestine are referred to as the gut microbiome (GMB). Functionally it behaves as a metabolic organ that communicates with, and complements, our own human metabolic apparatus. While the relationship between the GMB and kidney stone disease (KSD) has not been investigated, dysbiosis of the GMB has been associated with diabetes, obesity and cardiovascular disease. In this pilot study we sought to identify unique changes in the GMB of kidney stone patients compared to patients without KSD. With an IRB-approved protocol we enrolled 29 patients into our pilot study. 23 patients were kidney stone formers and six were non-stone forming controls. Specimens were collected after a 6h fast and were flash frozen in dry ice and then stored at -80 °C. Microbiome: determination of bacterial abundance was by analysis of 16 s rRNA marker gene sequences using next generation sequencing. Sequencing of the GMB identified 178 bacterial genera. The five most abundant enterotypes within each group made up to greater than 50 % of the bacterial abundance identified. Bacteroides was 3.4 times more abundant in the KSD group as compared to control (34.9 vs 10.2 %; p = 0.001). Prevotella was 2.8 times more abundant in the control group as compared to the KSD group (34.7 vs 12.3 %; p = 0.005). In a multivariate analysis including age, gender, BMI, and DM, kidney stone disease remained an increased risk for high prevalence for Bacteroides (OR = 3.26, p = 0.033), whereas there was an inverse association with Prevotella (OR = 0.37, p = 0.043). There were no statistically significant differences in bacterial abundance levels for Bacteroides or Prevotella when comparing patients with and without DM, obesity (BMI >30), HTN or HLD. 11 kidney stone patients completed 24 h urine analysis at the time of this writing. Looking at the bacterial genuses with at least 4 % abundance in the kidney stone group, Eubacterium was inversely correlated with oxalate levels (r = -0.60, p < 0.06) and Escherichia trended to an inverse correlation with citrate (r = -0.56, p < 0.08). We also compared bacterial abundance between uric acid (UA) stone formers (n = 5) and non UA stone formers (n = 18) and found no significant difference between them. We identified two genus of bacteria in the GMB that had significant association with KSD. Interestingly, components of the 24-h urine appear to be correlated to bacterial abundance. These preliminary studies for the first time associate differences in the GMB with kidney stone formation. Further studies are warranted to evaluate the potential causative role of preexisting dysbiosis in kidney stone disease.

Keywords: Gut microbiome; Kidney stones; Nephrolithiasis; Urolithiasis.

Fig. 1

a Heat map comparing the microbiome between patients with kidney stone disease (N = 23, red) and control (N = 6, green). The subjects are grouped by phylogeny and thereby not numerically. Note the clustering of Bacteroides and the Prevotella genera with the two groups of patients. b Highlighted heat map demonstrating the 5 most abundant genera in the kidney stone group. Note the clustering of Bacteroides and the Prevotella genera among the two groups of patients

Fig. 1

a Heat map comparing the microbiome between patients with kidney stone disease (N = 23, red) and control (N = 6, green). The subjects are grouped by phylogeny and thereby not numerically. Note the clustering of Bacteroides and the Prevotella genera with the two groups of patients. b Highlighted heat map demonstrating the 5 most abundant genera in the kidney stone group. Note the clustering of Bacteroides and the Prevotella genera among the two groups of patients

Fig. 2

a Gut microbiome abundance plot: Bacteroides was 3.4 times more abundant in the KSD group as compared to control (34.9 vs 10.2 %; p = 0.001). Prevotella was 2.8 times more abundant in the control group as compared to the KSD group (34.7 vs 12.3 %; p = 0.005). b The composition of the microbiota between kidney stone formers and non-stone forming controls. Percentage of each bacteria genus between cases (n = 23) and controls (n = 6) was plotted in the bar chart. The Wilcoxon Mann–Whitney tests with p < 0.05 were highlighted in bold. Genera with less than 500 of total reads were not presented

Fig. 2

a Gut microbiome abundance plot: Bacteroides was 3.4 times more abundant in the KSD group as compared to control (34.9 vs 10.2 %; p = 0.001). Prevotella was 2.8 times more abundant in the control group as compared to the KSD group (34.7 vs 12.3 %; p = 0.005). b The composition of the microbiota between kidney stone formers and non-stone forming controls. Percentage of each bacteria genus between cases (n = 23) and controls (n = 6) was plotted in the bar chart. The Wilcoxon Mann–Whitney tests with p < 0.05 were highlighted in bold. Genera with less than 500 of total reads were not presented