Session Type: ACR Poster Session C
Session Time: 9:00AM-11:00AM
Background/Purpose: The adaptive immune response in Rheumatoid arthritis (RA) is influenced by an interaction between host genetics and environment, particularly the host microbiome. To define the role of host microbiome, we characterized intestinal microbiome signatures in patients with RA.
Methods: To identify an RA biomarker profile, fecal samples from 40 RA patients and 32 healthy non-RA comparator subjects were sequenced for the 16S ribosomal DNA. Bray-Curtis distances were constructed and PERMANOVA was used to test for an association between variables of interest and the overall microbiota composition.PICRUSt was used to infer the abundance of functional categories (KEGG pathways) based on the 16S rRNA data, depending upon which differential abundance analysis was performed. Differential abundance analysis was also performed using LEfSe software. The machine learning algorithm ‘Random Forest’ was used to build a predictive model, and identify the most discriminatory taxa between patients and controls.
Results: Patients with RA exhibited decreased gut microbial diversity compared to controls. Increased rheumatoid factor levels and disease duration were associated with decreased species richness and diversity (P<0.05 and P<0.1 respectively) (Fig 1A). PERMANOVA based on Bray-Curtis distance showed that the structure of the microbiota of patients with RA differed significantly from control subjects (Fig 1B). A taxon-level analysis suggested an expansion of the rare taxa, Actinobacteria, with a decrease in abundant taxa in patients with RA compared to controls. The abundance of Actinobacteria correlated strongly with high levels of IL-17A. Prediction models based on the Random Forests algorithm suggested that 3 genera segregated with RA. Increased abundance of Actinobacteria was associated with decrease in the expression of tight junction protein in epithelial cells and abundance of metabolite alpha aminoadipic, a marker for age-associated changes in collagen.
Conclusion: These observations suggest dysbiosis in patients with RA resulting from the abundance of certain rare bacterial lineages. A correlation between the intestinal microbiota and metabolic signatures could determine a predictive profile for disease causation, progression, and drug efficacy.
To cite this abstract in AMA style:Chen J, Davis JM III, Matteson EL, Taneja V. An Expansion of Rare Lineage Intestinal Microbes Characterize Rheumatoid Arthritis [abstract]. Arthritis Rheumatol. 2015; 67 (suppl 10). https://acrabstracts.org/abstract/an-expansion-of-rare-lineage-intestinal-microbes-characterize-rheumatoid-arthritis/. Accessed January 29, 2020.
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ACR Meeting Abstracts - https://acrabstracts.org/abstract/an-expansion-of-rare-lineage-intestinal-microbes-characterize-rheumatoid-arthritis/