Gut dysbiosis in experimental kidney disease: a meta-analysis of rodent repository data

Randall, D.W., Kieswich, J., Hoyles, L. ORCID: 0000-0002-6418-342X, McCafferty, K., Curtis, M. and Yaqoob, M.M., 2023. Gut dysbiosis in experimental kidney disease: a meta-analysis of rodent repository data. Journal of the American Society of Nephrology. ISSN 1046-6673

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Abstract

Background: Single-cohort rodent studies have yielded insights into host:microbiome relationships in various disease processes, but their relevance is limited by cohort and cage effects. In nephrology, rodent studies have popularized the notion that uremia may induce pathological changes in the gut microbiota which contribute to progression of kidney disease.

Methods: All data describing the molecular characterization of the gut microbiota in rodents with and without experimental kidney disease were downloaded from two online repositories and re-analyzed using the DADA2 and Phyloseq packages in R. Data were analyzed 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). No microbial trends were seen universally in kidney disease animals, but some (increased alpha diversity, relative decreases in Lachnospiraceae and Lactobacillus, increases in other Clostridia and opportunistic taxa) were seen in many cohorts, and may represent the effects of kidney disease on the gut microbiome.

Discussion: We argue that there is inadequate evidence that kidney disease causes reproducible patterns of dysbiosis. We advocate meta-analysis of repository data as a way of identifying broad themes that transcend experimental variation.

Item Type: Journal article
Publication Title: Journal of the American Society of Nephrology
Creators: Randall, D.W., Kieswich, J., Hoyles, L., McCafferty, K., Curtis, M. and Yaqoob, M.M.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 21 January 2023
ISSN: 1046-6673
Identifiers:
NumberType
10.1681/asn.0000000000000071DOI
1728423Other
Divisions: Schools > School of Science and Technology
Record created by: Laura Ward
Date Added: 03 Mar 2023 10:20
Last Modified: 03 Mar 2023 10:20
URI: https://irep.ntu.ac.uk/id/eprint/48451

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