Alterations to the Gut Microbiota and Their Correlation With Inflammatory Factors in Chronic Kidney Disease

Abstract

Alterations to the gut microbiota have been previously suggested to be tightly linked to chronic systemic inflammation, which is a major contributing factor to complications and disease progression in chronic kidney disease (CKD). Nevertheless, the effect of gut dysbiosis on the pathogenesis and/or production of inflammatory factors in CKD has not been extensively studied to date. In the present study, we conducted 16S ribosomal DNA pyrosequencing using fecal microbiota samples and analyzed the production of serum inflammatory factors in 50 patients with CKD and 22 healthy control (HC) subjects. The results revealed that compared to the HC subjects, patients with CKD exhibited a significant reduction in the richness and structure of their fecal microbiota. At the phylum level, compared to the HC group, patients with CKD also presented reduced abundance of Actinobacteria but increased abundance of Verrucomicrobia. Moreover, the genera Lactobacillus, Clostridium IV, Paraprevotella, Clostridium sensu stricto, Desulfovibrio, and Alloprevotella were enriched in the fecal samples of patients with CKD, while Akkermansia and Parasutterella were enriched in those of the HC subjects. The abundance of Akkermansia in the CKD group was significantly lower than that in the HC group (3.08 vs. 0.67%); this decrease in the abundance of Akkermansia, an important probiotic, in patients with CKD is a striking discovery as it has not been previously reported. Finally, we analyzed whether these changes to the fecal microbiota correlated with CKD clinical characteristics and/or the production of known inflammatory factors. Altered levels of the microbiota genera Parasutterella, Lactobacillus, Paraprevotella, Clostridium sensu stricto, and Desulfovibrio were shown to be correlated with CKD disease-severity indicators, including the estimated glomerular filtration rate. Most notably, Akkermansia was significantly negatively correlated with the production of interleukin-10. The results of the present study suggest that microbiota dysbiosis may promote chronic systemic inflammation in CKD. Furthermore, they support that modifying the gut microbiota, especially Akkermansia, may be a promising potential therapeutic strategy to attenuate the progression of, and/or systemic inflammation in, CKD.

Keywords: 16S rDNA deep sequencing; Akkermansia; chronic kidney disease; gut microbiota; inflammatory factors.

Figure 1

Fecal microbiota alpha- and beta-diversity in patients with chronic kidney disease (CKD) and healthy control (HC) subjects. The depicted box plots show differences in the fecal microbiome diversity indices between the CKD and HC groups, as assessed using (A) Goods coverage diversity and (B) Phylogenetic Diversity (PD) whole-tree indices. Each box plot represents the median, interquartile range, minimum, and maximum values. (C,D) The level of similarity between the fecal microbial communities detected in the CKD (blue) and HC (orange) groups was assessed via (C) an unweighted Analysis of similarity (ANOSIMs) and (D) a principal coordinates analysis (PCoA; based on the UniFrac distance matrix). Respective ANOSIM R values show community variation between the compared groups, and significant P-values are indicated. Each symbol represents a sample.

Figure 2

Taxonomic differences in the fecal microbiota exhibited by patients with chronic kidney disease (CKD) and healthy control (HC) subjects. (A) A Linear discriminant analysis (LDA; (log10) > 2) and effect size (LEfSe) analysis revealed significant differences (P < 0.05) in the fecal microbiota exhibited by the CKD (blue, negative score) and HC (red, positive score) groups. These analyses revealed the most differentially abundant taxa at the level of bacterial (B) phylum (p), class (c), order (o), family (f), and (C) genus (g) between the CKD (green) and HC (purple) groups.

Figure 3

Receiver operating characteristic curve (ROC) analysis of the sensitivity and specificity of the differentially abundant genera as diagnostic factors for chronic kidney disease (CKD). The conducted analysis suggests that the relative abundances of (A) Akkermansia, (B) Lactobacillus, and most particularly, (C) of both Akkermansia and Lactobacillus, are likely promising diagnostic factors to distinguish between patients with CKD and healthy control (HC) subjects.

Figure 4

Heatmaps showing correlations between differentially abundant microbiota genera and chronic kidney disease (CKD) clinical parameters. Correlations were demonstrated between various differentially abundant fecal microbiota genera and (A) the specified CKD clinical characteristics, and (B) the production of inflammatory cytokines. BUN, blood urea nitrogen; CO₂CP, carbon dioxide combining power; CysC, Cystatin C; eGFR, estimated glomerular filtration rate; IL, Interleukin; SCr, Serum creatinine. Spearman test, *P < 0.05, **P < 0.01.

Figure 5

Functional predictions for the fecal microbiome exhibited by the patients with chronic kidney disease (CKD) and the healthy control (HC) subjects.