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Circulating regulatory B cell subsets in patients with neuromyelitis optica spectrum disorders

Overview of attention for article published in Neurological Sciences, April 2017
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Title
Circulating regulatory B cell subsets in patients with neuromyelitis optica spectrum disorders
Published in
Neurological Sciences, April 2017
DOI 10.1007/s10072-017-2932-7
Pubmed ID
Authors

Jinming Han, Li Sun, Zhongkun Wang, Xueli Fan, Lifang Wang, Yang-yang Song, Jie Zhu, Tao Jin

Abstract

This study analyzed the populations of three different subsets of regulatory B cells (Bregs) in the peripheral blood mononuclear cells (PBMCs) of patients with neuromyelitis optica spectrum disorders (NMOSDs) and explored the relationship between the changes in these subsets of Bregs and the severity of NMOSD. A total of 22 patients with relapsed NMOSDs before treatment were recruited in our study, along with 20 age and gender-matched healthy controls, from May 2015 to March 2016. The percentages and numbers for three different subsets of Bregs including the CD19(+)CD24(hi)CD38(hi), CD19(+)CD24(hi)CD27(+), and CD19(+)CD5(+)CD1d(hi) populations were evaluated in parallel by flow cytometry. Afterwards, correlations between the change of three different subsets of Bregs and disease severity were analyzed. We found significantly lower percentages of CD19(+)CD24(hi)CD38(hi) and CD19(+)CD5(+)CD1d(hi) Bregs in NMOSDs patients than in healthy individuals. In contrast, the CD19(+)CD24(hi)CD27(+) Bregs population was significantly higher in NMOSDs patients than in healthy individuals. However, the three different Bregs subsets showed no significant correlation with expanded disability status scale (EDSS) or annualized relapse rate (ARR). Our findings suggest that the subsets of Bregs may play complex roles in the pathogenesis of NMOSDs and are not correlated with clinical disease severity. Further insights into the potential role of subsets of Bregs could increase our basic knowledge of NMOSDs pathogenesis.

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Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 22%
Researcher 4 17%
Student > Ph. D. Student 4 17%
Other 2 9%
Lecturer 1 4%
Other 0 0%
Unknown 7 30%
Readers by discipline Count As %
Medicine and Dentistry 4 17%
Immunology and Microbiology 3 13%
Nursing and Health Professions 2 9%
Agricultural and Biological Sciences 2 9%
Neuroscience 2 9%
Other 1 4%
Unknown 9 39%