Title |
Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis
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Published in |
Cell Reports, September 2016
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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
Geographical breakdown
Country | Count | As % |
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United States | 5 | 36% |
Sweden | 1 | 7% |
Unknown | 8 | 57% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 8 | 57% |
Scientists | 5 | 36% |
Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
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% |