Longitudinal Pilot Evaluation of the Gut Microbiota Comparing Patients With and Without Chronic Kidney Disease

Abstract

Objective

The gut microbiota contributes to metabolic diseases, such as diabetes and hypertension, but is poorly characterized in chronic kidney disease (CKD).

Design and Methods

We enrolled 24 adults within household pairs, in which at least one member had self-reported kidney disease, diabetes, or hypertension. CKD was classified based on estimated glomerular filtration rate < 60 mL/min/1.73 m² or urine-albumin-to-creatinine ratio of ≥ 30 mg/g. Participants collected stool and dietary recalls seasonally over a year. Gut microbiota was characterized using 16s rRNA and metagenomic sequencing.

Results

Ten participants had CKD (42%) with a median (interquartile range) estimated glomerular filtration rate of 49 (44, 54) mL/min/1.73 m². By 16s rRNA sequencing, there was moderate to high intraclass correlation (ICC = 0.63) for seasonal alpha diversity (Shannon index) within individuals and modest differences by season (P < .01). ICC was lower with metagenomics, which has resolution at the species level (ICC = 0.26). There were no differences in alpha or beta diversity by CKD with either method. Among 79 genera, Frisingicoccus, Tuzzerella, Faecalitalea, and Lachnoclostridium had lower abundance in CKD, while Collinsella, Lachnospiraceae_ND3007, Veillonella, and Erysipelotrichaceae_UCG_003 were more abundant in CKD (each nominal P < .05) using 16s rRNA sequencing. Higher Collinsella and Veillonella and lower Lachnoclostridium in CKD were also identified by metagenomics. By metagenomics, Coprococcus catus and Bacteroides stercoris were more and less abundant in CKD, respectively, at false discovery rate corrected P = .02.

Conclusions

We identified candidate taxa in the gut microbiota associated with CKD. High ICC in individuals with modest seasonal impacts implies that follow-up studies may use less frequent sampling.