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Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis

Overview of attention for article published in Cell Reports, September 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

news
7 news outlets
blogs
1 blog
twitter
15 tweeters
facebook
1 Facebook page

Readers on

mendeley
19 Mendeley
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Title
Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis
Published in
Cell Reports, September 2016
DOI 10.1016/j.celrep.2016.08.036
Pubmed ID
Authors

Sandra Hellberg, Daniel Eklund, Danuta R. Gawel, Mattias Köpsén, Huan Zhang, Colm E. Nestor, Ingrid Kockum, Tomas Olsson, Thomas Skogh, Alf Kastbom, Christopher Sjöwall, Magnus Vrethem, Irene Håkansson, Mikael Benson, Maria C. Jenmalm, Mika Gustafsson, Jan Ernerudh, Hellberg, Sandra, Eklund, Daniel, Gawel, Danuta R, Köpsén, Mattias, Zhang, Huan, Nestor, Colm E, Kockum, Ingrid, Olsson, Tomas, Skogh, Thomas, Kastbom, Alf, Sjöwall, Christopher, Vrethem, Magnus, Håkansson, Irene, Benson, Mikael, Jenmalm, Maria C, Gustafsson, Mika, Ernerudh, Jan

Abstract

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS and has a varying disease course as well as variable response to treatment. Biomarkers may therefore aid personalized treatment. We tested whether in vitro activation of MS patient-derived CD4+ T cells could reveal potential biomarkers. The dynamic gene expression response to activation was dysregulated in patient-derived CD4+ T cells. By integrating our findings with genome-wide association studies, we constructed a highly connected MS gene module, disclosing cell activation and chemotaxis as central components. Changes in several module genes were associated with differences in protein levels, which were measurable in cerebrospinal fluid and were used to classify patients from control individuals. In addition, these measurements could predict disease activity after 2 years and distinguish low and high responders to treatment in two additional, independent cohorts. While further validation is needed in larger cohorts prior to clinical implementation, we have uncovered a set of potentially promising biomarkers.

Twitter Demographics

The data shown below were collected from the profiles of 15 tweeters 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 5%
United Kingdom 1 5%
Unknown 17 89%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 32%
Student > Ph. D. Student 4 21%
Researcher 3 16%
Professor 2 11%
Student > Bachelor 2 11%
Other 2 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 32%
Biochemistry, Genetics and Molecular Biology 3 16%
Medicine and Dentistry 3 16%
Unspecified 2 11%
Immunology and Microbiology 2 11%
Other 3 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 63. 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 29 November 2017.
All research outputs
#164,991
of 8,834,354 outputs
Outputs from Cell Reports
#426
of 4,334 outputs
Outputs of similar age
#9,650
of 254,550 outputs
Outputs of similar age from Cell Reports
#36
of 257 outputs
Altmetric has tracked 8,834,354 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,334 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.4. This one has done particularly well, scoring higher than 90% 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 254,550 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 96% of its contemporaries.
We're also able to compare this research output to 257 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.