↓ Skip to main content

PLOS

Antibody-Mediated Inhibition of TNFR1 Attenuates Disease in a Mouse Model of Multiple Sclerosis

Overview of attention for article published in PLOS ONE, February 2014
Altmetric Badge

Mentioned by

twitter
3 X users

Readers on

mendeley
77 Mendeley
Title
Antibody-Mediated Inhibition of TNFR1 Attenuates Disease in a Mouse Model of Multiple Sclerosis
Published in
PLOS ONE, February 2014
DOI 10.1371/journal.pone.0090117
Pubmed ID
Authors

Sarah K. Williams, Olaf Maier, Roman Fischer, Richard Fairless, Sonja Hochmeister, Aleksandar Stojic, Lara Pick, Doreen Haar, Sylvia Musiol, Maria K. Storch, Klaus Pfizenmaier, Ricarda Diem

Abstract

Tumour necrosis factor (TNF) is a proinflammatory cytokine that is known to regulate inflammation in a number of autoimmune diseases, including multiple sclerosis (MS). Although targeting of TNF in models of MS has been successful, the pathological role of TNF in MS remains unclear due to clinical trials where the non-selective inhibition of TNF resulted in exacerbated disease. Subsequent experiments have indicated that this may have resulted from the divergent effects of the two TNF receptors, TNFR1 and TNFR2. Here we show that the selective targeting of TNFR1 with an antagonistic antibody ameliorates symptoms of the most common animal model of MS, experimental autoimmune encephalomyelitis (EAE), when given following both a prophylactic and therapeutic treatment regime. Our results demonstrate that antagonistic TNFR1-specific antibodies may represent a therapeutic approach for the treatment of MS in the future.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Unknown 76 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 14 18%
Student > Ph. D. Student 12 16%
Student > Master 11 14%
Researcher 8 10%
Student > Doctoral Student 7 9%
Other 10 13%
Unknown 15 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 22%
Agricultural and Biological Sciences 16 21%
Medicine and Dentistry 9 12%
Neuroscience 6 8%
Immunology and Microbiology 4 5%
Other 7 9%
Unknown 18 23%