Participation of gut microbiota and bacterial translocation in chronic systemic inflammation in recently diagnosed rheumatoid arthritis patients

Abstract

The objective of this study was to investigate the link between gut microbiota (GM) dysbiosis, gut inflammation, and bacterial translocation (BT) in recently diagnosed rheumatoid arthritis (RA). This case-control, observational study prospectively recruited recently diagnosed (<12 months) RA patients and age-matched healthy controls (HC) from two French hospitals between July 2014 to March 2018. The primary objective was to investigate GM composition in each group using 16S rRNA sequencing and metaproteomics approaches. Three plasmatic BT markers (sCD14, LPS-binding protein, and number of 16S rRNA gene copies) and one intestinal permeability marker (I-FABP) were quantified in blood samples. Twenty-five were included in each group, and 50 stools and blood samples were analyzed. 16S rRNA gene analysis showed an decrease in Coprococcus in RA patients after Body Mass Index and HLA status. Circulating bacterial DNA (number of copies of the 16S rRNA gene) and plasmatic I-FABP were higher in RA patients compared to HCs (p < 0.01), indicating increased BT and intestinal permeability in these patients. Metaproteomics from stool samples highlighted an increased host humoral immune response in RA, with elevated levels of inflammatory proteins (azurocidin, cathepsin G, neutrophil defensing 1). Gut inflammation may contribute to increased intestinal permeability, leading to BT into the systemic circulation and thus chronic inflammation.

Keywords: Bacterial translocation; Gut microbiota; Intestinal permeability; Rheumatoid arthritis.

Graphical abstract

Fig. 1

Description of bacterial communities of gut microbiota in rheumatoid arthritis (RA) patients (RA) (n = 25) and Healthy Controls (HC) (n = 25). (a) Barplot of overall repartition of phyla in gut microbiota for RA and HC. (b) Barplot of average relative frequencies of genera. Only genus > 1 % of OTUs in at least one stool from RA patients and HC were represented. The remaining genus are added to the group “other”. (c) Boxplot of Pseudomonadota phylum abundance (d) Boxplot of Coprococcus genus abundance. Significance presented in the graphs was calculated by univariate analysis and by a general linear model, adjusted on the BMI and HLA DR4 status. ns; non-significant; *, p = 0.0091.

Fig. 2

Comparison of bacterial translocation (BT) and gut permeability markers in patients with rheumatoid arthritis (RA) and healthy controls (HC). BT markers are compared between RA patients (n = 25) and HC (n = 25) for (A) 16S rDNA, (B) LPS-binding protein (LBP), (C) sCD14 and for (D) I-FABP. Significance presented in the graphs was calculated by univariate analysis and by a general linear model, adjusted on the BMI and HLA DR4 status. ns; non-significant; *, p ≤ 0.05.

Fig. 3

Heatmap of standardized proteins composition of fecal samples patients with rheumatoid arthritis (RA) (n = 12) and healthy controls (n = 12) stool. Proteins pathways are represented through all proteins detected (with at least 2 Spectral Count (SC)) and identified by metaproteomics analysis. Standardized relative frequencies of proteins pathways are used in order to see variations between groups even for low-abundant proteins. Proteins pathways are classified according to agglomerative hierarchical clustering with complete linkage. (A) the bacteria level or at (B) the host level.

Fig. 4

Comparison of number of copies of 16 s rRNA gene in patients with rheumatoid arthritis (RA) (n = 25) and healthy controls (HC) (n = 25) in accordance to Coprococcus genus abundance (Low Coprococcus (<10 %) and High Coprococcus ($\ge 10░\%\left)\right)$. Significance presented in the graphs was calculated by univariate analysis and by a general linear model. p values are indicated on graphs.