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An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis

Overview of attention for article published in Genome Medicine, April 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#18 of 1,611)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
45 news outlets
blogs
3 blogs
twitter
60 X users
patent
1 patent
facebook
6 Facebook pages
video
3 YouTube creators

Citations

dimensions_citation
607 Dimensions

Readers on

mendeley
506 Mendeley
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Title
An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis
Published in
Genome Medicine, April 2016
DOI 10.1186/s13073-016-0299-7
Pubmed ID
Authors

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

Abstract

The 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. To 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. Patients 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. These 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 60 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 506 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 <1%
Germany 1 <1%
Netherlands 1 <1%
Brazil 1 <1%
France 1 <1%
China 1 <1%
United Kingdom 1 <1%
Unknown 498 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 86 17%
Researcher 69 14%
Student > Master 63 12%
Student > Bachelor 51 10%
Other 31 6%
Other 72 14%
Unknown 134 26%
Readers by discipline Count As %
Medicine and Dentistry 88 17%
Biochemistry, Genetics and Molecular Biology 79 16%
Agricultural and Biological Sciences 67 13%
Immunology and Microbiology 58 11%
Nursing and Health Professions 22 4%
Other 44 9%
Unknown 148 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 406. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 September 2023.
All research outputs
#74,175
of 25,837,817 outputs
Outputs from Genome Medicine
#18
of 1,611 outputs
Outputs of similar age
#1,438
of 316,103 outputs
Outputs of similar age from Genome Medicine
#4
of 38 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,611 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 316,103 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.