Gut Dysbiosis in Experimental Kidney Disease: A Meta-Analysis of Rodent Repository Data

Abstract

Background 

Rodent studies have popularized the notion that uremia may induce pathologic changes in the gut microbiota that contribute to kidney disease progression. Although single-cohort rodent studies have yielded insights into host-microbiota relationships in various disease processes, their relevance is limited by cohort and other effects. We previously reported finding metabolomic evidence that batch-to-batch variations in the microbiome of experimental animals are significant confounders in an experimental study.

Methods 

To attempt to identify common microbial signatures that transcend batch variability and that may be attributed to the effect of kidney disease, we downloaded all data describing the molecular characterization of the gut microbiota in rodents with and without experimental kidney disease from two online repositories comprising 127 rodents across 10 experimental cohorts. We re-analyzed these data using the DADA2 and Phyloseq packages in R, a statistical computing and graphics system, and analyzed data both in a combined dataset of all samples and at the level of individual experimental cohorts.

Results 

Cohort effects accounted for 69% of total sample variance (p<0.001), substantially outweighing the effect of kidney disease (1.9% of variance, p=0.026). We found no universal trends in microbial population dynamics in animals with kidney disease, but observed some differences (increased alpha diversity, a measure of within-sample bacterial diversity; relative decreases in Lachnospiraceae and Lactobacillus; and increases in some Clostridia and opportunistic taxa) in many cohorts that might represent effects of kidney disease on the gut microbiota.

Conclusions 

These findings suggest that current evidence that kidney disease causes reproducible patterns of dysbiosis is inadequate. We advocate meta-analysis of repository data as a way of identifying broad themes that transcend experimental variation.