↓ Skip to main content

Role of TFH Cells in Promoting T Helper 17-Induced Neuroinflammation

Overview of attention for article published in Frontiers in immunology, February 2018
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
62 Dimensions

Readers on

mendeley
58 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Role of TFH Cells in Promoting T Helper 17-Induced Neuroinflammation
Published in
Frontiers in immunology, February 2018
DOI 10.3389/fimmu.2018.00382
Pubmed ID
Authors

James L. Quinn, Gaurav Kumar, Agnieshka Agasing, Rose M. Ko, Robert C. Axtell

Abstract

Both T cells and B cells are implicated in the pathology of multiple sclerosis (MS), but how these cells cooperate to drive disease remains unclear. Recent studies using experimental autoimmune encephalomyelitis (EAE) demonstrated that the TH17 pathway is correlated with increased numbers of ectopic B-cell follicles in the central nervous system (CNS). As follicular T helper (TFH) cells are regulators of B cell responses, we sought to examine the role of TFH cells in EAE induced by the transfer of myelin-specific TH17 cells (TH17-EAE). In this study, we first confirmed previous reports that B-cells are a major cell type infiltrating the CNS during TH17-EAE. In addition, we found that B cells contribute to the severity of TH17-EAE. Class-switched B-cells in the CNS were positively correlated with disease and, strikingly, the severity TH17-EAE was diminished in B cell deficient mice. We next focused on the role TFH cells play in TH17-EAE. We found substantial numbers of CXCR5+PD1+CD4+TFH cells in the CNS tissue of TH17-EAE mice and that at the peak of disease, the number of infiltrating TFHs was correlated with the number of infiltrating B-cells. Using congenic CD45.1+donor mice and CD45.2+recipient mice, we determined that the TFH cells were recipient-derived, whereas IL-17+cells were donor-derived. We assessed whether myelin-specific TFH cells are capable of inducing EAE in recipient mice and found that transferring TFH cells failed to induce EAE. Finally, we tested the effects of blocking TFH trafficking in TH17-EAE using an antagonistic antibody against CXCL13, the chemokine ligand for CXCR5 on TFH cells. We found anti-CXCL13 treatment significantly reduced TH17-EAE disease. This treatment blocked CD4+T cells from entering the CNS, but had no effect on infiltration of B cells. Strikingly, this antibody treatment had no measurable effect on TH17 disease in B cell-deficient mice. These data demonstrate that infiltrating TFH cells are a key cell type that contributes to an inflammatory B cell response in TH17-EAE and provide evidence for targeting TFH cells as a treatment for neuro-autoimmune diseases like MS.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 58 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 24%
Student > Bachelor 10 17%
Researcher 8 14%
Student > Doctoral Student 6 10%
Student > Master 3 5%
Other 7 12%
Unknown 10 17%
Readers by discipline Count As %
Immunology and Microbiology 13 22%
Neuroscience 8 14%
Medicine and Dentistry 7 12%
Biochemistry, Genetics and Molecular Biology 6 10%
Agricultural and Biological Sciences 4 7%
Other 10 17%
Unknown 10 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 15 March 2018.
All research outputs
#21,320,623
of 26,184,649 outputs
Outputs from Frontiers in immunology
#25,543
of 33,037 outputs
Outputs of similar age
#272,350
of 347,285 outputs
Outputs of similar age from Frontiers in immunology
#587
of 688 outputs
Altmetric has tracked 26,184,649 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 33,037 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 14th percentile – i.e., 14% of its peers scored the same or lower than it.
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 347,285 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 688 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.