Gut Mycobiome in Patients With Chronic Kidney Disease Was Altered and Associated With Immunological Profiles

Abstract

Objectives: Mounting evidence suggests that bacterial dysbiosis and immunity disorder are associated with patients with chronic kidney disease (CKD), but the mycobiome is beginning to gain recognition as a fundamental part of our microbiome. We aim to characterize the profile of the mycobiome in the gut of CKD patients and its correlation to serum immunological profiles.

Methods and materials: Ninety-two CKD patients and sex-age-body mass index (BMI)-matched healthy controls (HCs) were recruited. Fresh samples were collected using sterile containers. ITS transcribed spacer ribosomal RNA gene sequencing was performed on the samples. An immunoturbidimetric test was used to assess the serum levels of immunological features.

Results: The CKD cohort displayed a different microbial community from that in the HC cohort according to principal coordinate analysis (PCoA). (P=0.001). The comparison of the two cohorts showed that the CKD cohort had significantly higher gut microbial richness and diversity (P<0.05). The CKD cohort had lower abundances of Candida, Bjerkandera, Rhodotorula, and Ganoderma compared to the HC cohort, while it had higher Saccharomyces (P<0.05). However, the microbial community alteration was inconsistent with the severity of kidney damage in patients, as only patients in CKD stage 1~3 had differed microbial community concerning for HCs based on PCoA (P<0.05). The serum concentration of the kappa light chain in CKD patients was positively associated with Saccharomyces, whereas the it was negatively associated with Ganoderma (P<0.05).

Conclusions: Not only was gut mycobiome dysbiosis observed in CKD patients, but the dysbiosis was also associated with the immunological disorder. These findings suggest that therapeutic strategies targeting gut mycobiome might be effective.

Keywords: Candida; Saccharomyces; chronic kidney disease; immunity disorder; microbial dysbiosis; mycobiome.

Figure 1

Microbial community, diversity, composition, and differed genera in the cohorts of CKD and HC. (A) PCoA based on Bray–Curtis distances at the OTU level showed different microbial compositions between groups of CKD patients and HCs (P < 0.05). Permutational multivariate analysis of variance (PERMANOVA) was performed for statistical comparisons of samples in the two cohorts. P-value was adjusted by the Benjamini–Hochberg FDR. (B) Bacterial richness and diversity measured by Chao1, Shannon, and Simpson were calculated at the microbial OTU level. The CKD patients had significantly higher levels of bacterial richness and diversity. The Wilcoxon rank-sum test was performed and adjusted by the Benjamini–Hochberg FDR. ** indicates P < 0.01. (C) Microbial profile at the phylum and genus levels. Sankey plot representing the overall gut mycobiome composition and corresponding abundance area for CKD patients and HCs. The taxonomic classification levels of phylum and genus are displayed. The top ten most abundant genera and their affiliated phyla are shown in the Sankey plot. (D) Microbial genera that were differentially abundant between CKD patients and HCs. Only the genera with above 1% are displayed. P-value was calculated using the Wilcoxon rank-sum test and adjusted by the Benjamini and Hochberg FDR. *, **, and *** indicate P < 0.05, P < 0.01, and P < 0.001, respectively.

Figure 2

Microbial community, diversity, composition, and Saccharomyces in the subgroups according to CKD stages and HC. (A) PCoA based on Bray–Curtis distances at the OTU level showed different microbial compositions between the subgroups of patients’ renal function damage and HCs. Permutational multivariate analysis of variance (PERMANOVA) was performed for statistical comparisons of samples in the two cohorts. Patients with normal- or high-eGFR CKD/moderate CKD/end-stage CKD showed different microbial communities compared to HCs/mild CKD/moderate CKD (P < 0.05). P-value was adjusted by the Benjamini and Hochberg FDR. (B) Bacterial richness and diversity measured by Chao1, Shannon, and Simpson were calculated at the microbial OTU level. Chao1 showed significantly higher in normal or high eGFR CKD in relation to HCs/moderate CKD (P < 0.05). Wilcoxon rank-sum test was performed and adjusted by the Benjamini and Hochberg FDR. * and ** indicate P < 0.05 and P < 0.01, respectively. (C) Comparison of the abundances of Saccharomyes in CKD patients from normal or high eGFR CKD to end-stage CKD and HC. *, **, and *** indicate P < 0.05, P < 0.01, and P < 0.001, respectively.

Figure 3

Gut mycobiome correlation to immunological profiles. Spearman correlation analysis was performed on the abundant bacterial genera (>1% relative abundances) that displayed a significant difference between CKD patients and HCs and the disease profiles that showed significant difference between CKD patients and HCs. The correlations of two variables with values of P < 0.05 are displayed. *, and ** indicate P < 0.05 and P < 0.01 respectively.