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T-bet+CD27+CD21– B cells poised for plasma cell differentiation during antibody-mediated rejection of kidney transplants
Kevin Louis, … , Carmen Lefaucheur, Diana Metes
Kevin Louis, … , Carmen Lefaucheur, Diana Metes
Published May 25, 2021
Citation Information: JCI Insight. 2021;6(12):e148881. https://doi.org/10.1172/jci.insight.148881.
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Research Article Immunology Transplantation

T-bet+CD27+CD21– B cells poised for plasma cell differentiation during antibody-mediated rejection of kidney transplants

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Abstract

Alloimmune responses driven by donor-specific antibodies (DSAs) can lead to antibody-mediated rejection (ABMR) in organ transplantation. Yet, the cellular states underlying alloreactive B cell responses and the molecular components controlling them remain unclear. Using high-dimensional profiling of B cells in a cohort of 96 kidney transplant recipients, we identified expanded numbers of CD27+CD21– activated memory (AM) B cells that expressed the transcription factor T-bet in patients who developed DSAs and progressed to ABMR. Notably, AM cells were less frequent in DSA+ABMR– patients and at baseline levels in DSA– patients. RNA-Seq analysis of AM cells in patients undergoing ABMR revealed these cells to be poised for plasma cell differentiation and to express restricted IGHV sequences reflective of clonal expansion. In addition to T-bet, AM cells manifested elevated expression of interferon regulatory factor 4 and Blimp1, and upon coculture with autologous T follicular helper cells, differentiated into DSA-producing plasma cells in an IL-21–dependent manner. The frequency of AM cells was correlated with the timing and severity of ABMR manifestations. Importantly, T-bet+ AM cells were detected within kidney allografts along with their restricted IGHV sequences. This study delineates a pivotal role for AM cells in promoting humoral responses and ABMR in organ transplantation and highlights them as important therapeutic targets.

Authors

Kevin Louis, Elodie Bailly, Camila Macedo, Louis Lau, Bala Ramaswami, Alexander Chang, Uma Chandran, Douglas Landsittel, Xinyan Gu, Geetha Chalasani, Adriana Zeevi, Parmjeet Randhawa, Harinder Singh, Carmen Lefaucheur, Diana Metes

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Figure 1

High-dimensional flow cytometry analyses of MBCs in kidney transplant patients.

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High-dimensional flow cytometry analyses of MBCs in kidney transplant pa...
(A) t-SNE projections were generated using a concatenated file of n = 79,200 MBCs from HC (n = 4), DSA– (n = 20), DSA+ABMR– (n = 20), and DSA+ABMR+ (n = 20) patients; panels display expression levels of indicated markers (MFI). (B) t-SNE projections of MBC densities in the 4 groups using n = 19,800 cells from each group shown in panel A. (C) t-SNE map overlaid with 12 MBC clusters delineated by SPADE clustering of the concatenated file, as in panel A. (D) Heatmap showing the expression of markers for each MBC cluster according to transformed MFI ratio. (E) Stacked bar plot showing MBC cluster distribution based on SPADE clustering as in panel C. Clusters 3, 4, 6, 7, 9, 11, and 12 are significantly different in their proportions across the indicated groups. Kruskal-Wallis with Dunn’s posttest. (F) Representative examples of flow cytometry analysis and dot plot of percentages of CD21–T-bet+ cells in CD38lo B cells are displayed; HC (n = 17), DSA– (n = 48), DSA+ABMR– (n = 28), and DSA+ABMR+ (n = 20) patients. Kruskal-Wallis with Dunn’s posttest. **P < 0.01; ***P < 0.001; ****P < 0.0001. Each dot represents 1 subject and horizontal lines are mean values ± SEM. SPADE, spanning-tree progression analysis of density-normalized events; t-SNE, t-distributed stochastic neighbor embedding.

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