Back

Activation and clonal expansion of CD8+T cells in patients with anti-NMDAR encephalitis revealed by single-cell RNA sequencing analysis

Li, S.; Hu, X.; Yang, Y.; Wang, J.; He, Z.; Yu, L.; Hong, Z.; Zhou, D.; Li, J.

2023-07-31 neurology
10.1101/2023.07.27.23292878 medRxiv
Show abstract

BackgroundAnti-N-methyl-D-aspartate receptor encephalitis (NMDAR-E) is a common and severe antibody-mediated autoimmune encephalitis. While the roles of B cells and NMDAR antibodies in NMDAR-E have been extensively studied, the involvement of T cell subpopulations in the disease progression remains unclear. MethodsThis study conducted single-cell RNA sequencing, single-cell TCR sequencing, and flow cytometry to analyze the T cell subpopulations and their transcriptomic characteristics in NMDAR-E patients and control individuals. Furthermore, it explored the interaction between CD8+T cells and B cells through in vitro cell co-culture and cell communication analysis. ResultsThe study found activated CD8+T cell subpopulations in the cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) of NMDAR-E patients, with some subpopulations exhibiting significant TCR clonal expansion. Differential expression gene analysis revealed upregulation of genes related to cytotoxicity, tissue residency, Th1, IFN, or TCR signaling in certain activated CD8+T cell and CD4+ memory T cell subpopulations. In vitro co-culture experiments demonstrated that CD8+T cells from the PBMCs of NMDAR-E patients could induce apoptosis of their own B cells. Cell interaction analysis revealed the existence of interactions between KIR+CD8+T cells and B cell subpopulations in NMDAR-E patients. ConclusionThis study explored the changes and transcriptomic characteristics of activated CD8+T cell subpopulations in the CSF and PBMCs of NMDAR-E patients. Additionally, it discovered the impact of CD8+T cells from NMDAR-E patients on their own B cells, providing new evidence for the interaction between CD8+T cells and B cells.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.