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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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  • 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 (84th percentile)

Mentioned by

news
7 news outlets
blogs
1 blog
twitter
14 X users
facebook
1 Facebook page

Citations

dimensions_citation
39 Dimensions

Readers on

mendeley
54 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

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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Germany 1 2%
Unknown 52 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 22%
Student > Master 9 17%
Researcher 8 15%
Student > Bachelor 5 9%
Professor 3 6%
Other 9 17%
Unknown 8 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 20%
Agricultural and Biological Sciences 8 15%
Immunology and Microbiology 8 15%
Medicine and Dentistry 7 13%
Neuroscience 4 7%
Other 8 15%
Unknown 8 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 62. 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 18 October 2019.
All research outputs
#685,489
of 25,373,627 outputs
Outputs from Cell Reports
#1,539
of 12,955 outputs
Outputs of similar age
#13,241
of 348,359 outputs
Outputs of similar age from Cell Reports
#44
of 291 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,955 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 30.3. This one has done well, scoring higher than 88% 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 348,359 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 291 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.