An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis View Full Text


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Article Info

DATE

2016-04-21

AUTHORS

Jun Chen, Kerry Wright, John M. Davis, Patricio Jeraldo, Eric V. Marietta, Joseph Murray, Heidi Nelson, Eric L. Matteson, Veena Taneja

ABSTRACT

BackgroundThe adaptive immune response in rheumatoid arthritis (RA) is influenced by an interaction between host genetics and environment, particularly the host microbiome. Association of the gut microbiota with various diseases has been reported, though the specific components of the microbiota that affect the host response leading to disease remain unknown. However, there is limited information on the role of gut microbiota in RA. In this study we aimed to define a microbial and metabolite profile that could predict disease status. In addition, we aimed to generate a humanized model of arthritis to confirm the RA-associated microbe.MethodsTo identify an RA biomarker profile, the 16S ribosomal DNA of fecal samples from RA patients, first-degree relatives (to rule out environment/background as confounding factors), and random healthy non-RA controls were sequenced. Analysis of metabolites and their association with specific taxa was performed to investigate a potential mechanistic link. The role of an RA-associated microbe was confirmed using a human epithelial cell line and a humanized mouse model of arthritis.ResultsPatients with RA exhibited decreased gut microbial diversity compared with controls, which correlated with disease duration and autoantibody levels. A taxon-level analysis suggested an expansion of rare taxa, Actinobacteria, with a decrease in abundant taxa in patients with RA compared with controls. Prediction models based on the random forests algorithm suggested that three genera, Collinsella, Eggerthella, and Faecalibacterium, segregated with RA. The abundance of Collinsella correlated strongly with high levels of alpha-aminoadipic acid and asparagine as well as production of the proinflammatory cytokine IL-17A. A role for Collinsella in altering gut permeability and disease severity was confirmed in experimental arthritis.ConclusionsThese observations suggest dysbiosis in RA patients 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 and progression. More... »

PAGES

43

References to SciGraph publications

  • 2013-06-18. Innate immune recognition of the microbiota promotes host-microbial symbiosis in NATURE IMMUNOLOGY
  • 2013-08-25. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences in NATURE BIOTECHNOLOGY
  • 2015-07-27. The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment in NATURE MEDICINE
  • 2014-04-16. Dynamics and associations of microbial community types across the human body in NATURE
  • 2012-02-23. The gut anaerobe Faecalibacterium prausnitzii uses an extracellular electron shuttle to grow at oxic–anoxic interphases in THE ISME JOURNAL: MULTIDISCIPLINARY JOURNAL OF MICROBIAL ECOLOGY
  • 2015-03-29. Body mass index and the risk of rheumatoid arthritis: a systematic review and dose-response meta-analysis in ARTHRITIS RESEARCH & THERAPY
  • 2001-10. Random Forests in MACHINE LEARNING
  • 2014-06-10. The multifactorial role of neutrophils in rheumatoid arthritis in NATURE REVIEWS RHEUMATOLOGY
  • 2011-06-24. Metagenomic biomarker discovery and explanation in GENOME BIOLOGY
  • 2008-11-30. A core gut microbiome in obese and lean twins in NATURE
  • 2009-12-17. Influence of microbial environment on autoimmunity in NATURE IMMUNOLOGY
  • 2006-08. Mechanisms of Disease: genetic susceptibility and environmental triggers in the development of rheumatoid arthritis in NATURE REVIEWS RHEUMATOLOGY
  • 2011-07-23. Environmental Exposures and Rheumatoid Arthritis Risk in CURRENT RHEUMATOLOGY REPORTS
  • 2011-04-20. Enterotypes of the human gut microbiome in NATURE
  • 2011-07-21. Anti-CXCL5 therapy ameliorates IL-17-induced arthritis by decreasing joint vascularization in ANGIOGENESIS
  • 2012-09-26. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment in GENOME BIOLOGY
  • 2012-01-29. Five amino acids in three HLA proteins explain most of the association between MHC and seropositive rheumatoid arthritis in NATURE GENETICS
  • 2007-10-17. The Human Microbiome Project in NATURE
  • Identifiers

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    http://scigraph.springernature.com/pub.10.1186/s13073-016-0299-7

    DOI

    http://dx.doi.org/10.1186/s13073-016-0299-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1009016129

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27102666


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