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Identification of definitive serum biomarkers associated with disease activity in primary Sjögren’s syndrome

Overview of attention for article published in Arthritis Research & Therapy, May 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
1 news outlet
twitter
1 tweeter

Citations

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29 Dimensions

Readers on

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57 Mendeley
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Title
Identification of definitive serum biomarkers associated with disease activity in primary Sjögren’s syndrome
Published in
Arthritis Research & Therapy, May 2016
DOI 10.1186/s13075-016-1006-1
Pubmed ID
Authors

Ayumi Nishikawa, Katsuya Suzuki, Yoshiaki Kassai, Yuumi Gotou, Maiko Takiguchi, Takahiro Miyazaki, Keiko Yoshimoto, Hidekata Yasuoka, Kunihiro Yamaoka, Rimpei Morita, Akihiko Yoshimura, Tsutomu Takeuchi

Abstract

In this study, we sought to identify definitive biomarkers associated with disease activity in primary Sjögren's syndrome (pSS). Serum protein concentrations in pSS patients and healthy controls (HCs) were comprehensively screened using high-throughput proteomic analysis, and differentially expressed proteins were extracted. Correlation between differentially expressed proteins and European League Against Rheumatism Sjögren's Syndrome Disease Activity Index (ESSDAI) scores was analyzed and disease activity-associated biomarkers were identified. These biomarkers were validated by enzyme-linked immunosorbent assay (ELISA) in a separate pSS cohort. The serum concentrations of 1100 proteins were compared between 30 pSS patients and 30 HCs, with 82 differentially expressed proteins identified as pSS-associated proteins. Of these 82 proteins, 9 were identified as disease activity-associated biomarkers. These nine biomarkers underwent validation by ELISA in a separate pSS validation cohort (n = 58), with five proteins (CXCL13, TNF-R2, CD48, B-cell activating factor (BAFF), and PD-L2) subsequently being confirmed as candidate biomarkers. Of these five candidate biomarkers, CXCL13 exhibited the most significant correlation with the lymphadenopathy, glandular, and pulmonary domains of the ESSDAI. CXCL13, TNF-R2 and CD48 exhibited a positive correlation with the biological domain of the ESSDAI. TNF-R2 exhibited the most negative correlation with uptake in the submandibular gland on technetium 99m-pertechnetate salivary gland scintigraphy. Our approach successfully identified serum biomarkers associated with disease activity in pSS patients. These markers might be potential therapeutic targets in pSS patients.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 19%
Student > Ph. D. Student 10 18%
Student > Master 8 14%
Other 7 12%
Professor 5 9%
Other 11 19%
Unknown 5 9%
Readers by discipline Count As %
Medicine and Dentistry 27 47%
Agricultural and Biological Sciences 6 11%
Immunology and Microbiology 5 9%
Biochemistry, Genetics and Molecular Biology 4 7%
Neuroscience 2 4%
Other 5 9%
Unknown 8 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 31 May 2016.
All research outputs
#1,243,723
of 11,622,318 outputs
Outputs from Arthritis Research & Therapy
#310
of 1,602 outputs
Outputs of similar age
#44,927
of 277,695 outputs
Outputs of similar age from Arthritis Research & Therapy
#6
of 54 outputs
Altmetric has tracked 11,622,318 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,602 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 93% 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 277,695 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 83% of its contemporaries.
We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.