Gut flora metagenomic analysis coupled with metabolic and deep immune profiling in chronic kidney disease

Background. Perturbation of gut microbiota has been linked to chronic kidney disease (CKD), which was correlated with a sophisticated milieu of metabolic and immune dysregulation. Methods. To clarify the underlying host–microbe interaction in CKD, we performed multi-omics measurements, including systems-level gut microbiome, targeted serum metabolome and deep immunotyping, in a cohort of patients and non-CKD controls. Results. Our analyses on functional profiles of the gut microbiome showed a decrease in the diversity and abundance of carbohydrate-active enzyme (CAZyme) genes but an increase in the abundance of antibiotic resistance, nitrogen cycling enzyme and virulence factor genes in CKD. Moreover, models generated using measurements of serum metabolites (amino acids, bile acids and short-chain fatty acids) or immunotypes were predictive of renal impairment but less so than many of the functional profiles derived from gut microbiota, with the CAZyme genes being the top-performing model to accurately predict the early stage of diseases. In addition, co-occurrence analyses revealed coordinated host–microbe relationships in CKD. Specifically, the highest fractions of significant correlations were identified with circulating metabolites by several taxonomic and functional profiles of gut microbiome, while immunotype features were moderately associated with the abundance of microbiome-encoded metabolic pathways and serum levels of amino acids (e.g. B cell cluster tryptophan and B cell cluster tryptophan metabolism). Conclusion. Overall, our multi-omics integration revealed several signatures of systems-level gut microbiome in robust associations with host–microbe co-metabolites and renal function, which may have aetiological and diagnostic implications in CKD.