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Kidney Week

Abstract: TH-PO911

Sequential Changes of Gut Microbiota According to the Stages of CKD

Session Information

Category: CKD (Non-Dialysis)

  • 1903 CKD (Non-Dialysis): Mechanisms

Authors

  • Kim, Ji Eun, Seoul National University Hospital, Seoul, Korea (the Republic of)
  • Park, Ji In, Kangwon National University Hospital, Chuncheon-si,, Korea (the Republic of)
  • Cho, Hyunjeong, Chungbuk National University Hospital , Cheongju-si, chungcheongbuk-Do, Korea (the Republic of)
  • Kim, Dong Ki, Seoul National University Hospital, Seoul, Korea (the Republic of)
  • Yang, Seung Hee, Kidney Research Institute, Seoul National University, Seoul, Korea (the Republic of)
  • Lee, Jung Pyo, Seoul National University Boramae Medical Center, Seoul, Korea (the Republic of)
  • Kim, Yon Su, Seoul National University Hospital, Seoul, Korea (the Republic of)
  • Lee, Hajeong, Seoul National University Hospital, Seoul, Korea (the Republic of)
Background

Recent evidences suggest that the microbiome profile is altered in patients with end-stage renal disease (ESRD) compared to healthy population. However, sequential changes of gut microbiota according to the stages of chronic kidney disease (CKD) have been explored rarely.

Methods

We prospectively enrolled 139 patients including CKD patients underwent kidney biopsy, ESRD patients waiting for kidney transplantation, and 35 kidney donors from three tertiary hospitals. The composition of microbiota was analyzed using extracted metagenomic DNA from the feces by Illumina MiSeq system. Estimated glomerular filtration rate (eGFR) was calculated using CKD-EPI equation.

Results

Total of 194 subjects were enrolled and divided into 4 groups according to their renal function as follows; 55 healthy control, 47 CKD stage 1-2, 42 stage 3-5 without receiving dialysis, and 50 stage 5 with maintenance dialysis. The mean eGFR of each groups were 103.4±15.2, 93.3±17.4, 29.6±20.4, and 7.1±2.5 mL/min/1.73 m2, respectively. The bacterial operational taxonomic units, diversity and richness were significantly different among 4 groups. Next, we compared 35 genera, which account for more than 1% of the sample composition in at least 1/10 of the total samples, among groups. Fourteen of the 35 genus groups showed significant differences among groups. Among those genera, Alistipes, Pseudoflavonifractor, Ruminococcus_g4 and Hungatella showed statistically significant increasing trend according to CKD groups and Lachnospira, Dialister and Haemophilus showed statistically significant decreasing trend according to the CKD groups with or without CKD 5D. Blautia showed an increasing trend according to the CKD group, but when the CKD 5D was included, the trend disappeared. Compared with CKD3-5ND and CKD 5D, Prevotella, Bifidobacterium and Agathobacter decreased after dialysis, and Clostridium and Pseudoflavonifractor increased after dialysis. The genera showing a change by dialysis and the genera showing a trend according to CKD stage showed different patterns except for Pseudoflavonifractor.

Conclusion

We found specific fecal microbiotas that changed according to the CKD stage, and they differed from the microbiota which was altered by dialysis. Further studies on the association of these microbiotas with CKD progression are needed.