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Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis

Overview of attention for article published in Arthritis Research & Therapy, August 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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1 news outlet
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3 X users

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51 Mendeley
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Title
Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis
Published in
Arthritis Research & Therapy, August 2018
DOI 10.1186/s13075-018-1655-3
Pubmed ID
Authors

Rekha Narasimhan, Roxana Coras, Sara B. Rosenthal, Shannon R. Sweeney, Alessia Lodi, Stefano Tiziani, David Boyle, Arthur Kavanaugh, Monica Guma

Abstract

Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients' metabolomic profiles in blood, utilizing 1H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA). Nineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700 MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS. Analysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-α synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels. The relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 18%
Student > Ph. D. Student 7 14%
Student > Master 6 12%
Other 4 8%
Student > Bachelor 3 6%
Other 4 8%
Unknown 18 35%
Readers by discipline Count As %
Immunology and Microbiology 6 12%
Biochemistry, Genetics and Molecular Biology 6 12%
Agricultural and Biological Sciences 6 12%
Medicine and Dentistry 4 8%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 4 8%
Unknown 23 45%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 27 August 2018.
All research outputs
#3,063,285
of 25,385,509 outputs
Outputs from Arthritis Research & Therapy
#622
of 3,381 outputs
Outputs of similar age
#58,451
of 341,622 outputs
Outputs of similar age from Arthritis Research & Therapy
#24
of 69 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,381 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done well, scoring higher than 81% 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 341,622 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.