Characteristics of Gut Microbiota in Patients With Rheumatoid Arthritis in Shanghai, China

Front Cell Infect Microbiol. 2019 Oct 23:9:369. doi: 10.3389/fcimb.2019.00369. eCollection 2019.

Abstract

Little is known regarding differences in the gut microbiomes of rheumatoid arthritis (RA) patients and healthy cohorts in China. This study aimed to identify differences in the fecal microbiomes of 66 Chinese patients with RA and 60 healthy Chinese controls. The V3-V4 variable regions of bacterial 16S rRNA genes were sequenced with the Illumina system to define the bacterial composition. The alpha-diversity index of the microbiome of the RA patients was significantly lower than that of the control group. The bacterial genera Bacteroides (p = 0.02202) and Escherichia-Shigella (p = 0.03137) were more abundant in RA patients. In contrast, Lactobacillus (p = 0.000014), Alloprevotella (p = 0.0000008615), Enterobacter (p = 0.000005759), and Odoribacter (p = 0.0000166) were less abundant in the RA group than in the control group. Spearman correlation analysis of blood physiological measures of RA showed that bacterial genera such as Dorea and Ruminococcus were positively correlated with RF-IgA and anti-CCP antibodies. Furthermore, Alloprevotella and Parabacteroides were positively correlated with the erythrocyte sedimentation rate, and Prevotella-2 and Alloprevotella were positively correlated with C-reactive protein, both biomarkers of inflammation. These findings suggest that the gut microbiota may contribute to RA development via interactions with the host immune system.

Keywords: 16S rRNA gene sequencing; biomarker; gut microbiome; inflammation; rheumatoid arthritis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Arthritis, Rheumatoid / etiology*
  • Arthritis, Rheumatoid / metabolism
  • Bacteria / classification
  • Bacteria / genetics
  • Biomarkers
  • China / epidemiology
  • Computational Biology / methods
  • Disease Susceptibility*
  • Female
  • Gastrointestinal Microbiome*
  • Gene Expression Profiling
  • Humans
  • Inflammation Mediators / metabolism
  • Male
  • Metagenome
  • Metagenomics / methods
  • Middle Aged
  • RNA, Ribosomal, 16S / genetics
  • Young Adult

Substances

  • Biomarkers
  • Inflammation Mediators
  • RNA, Ribosomal, 16S