Alloreactive T cells temporarily increased in the peripheral blood of patients before liver allograft rejection

在肝移植排斥反应发生前,患者外周血中同种异体反应性T细胞会暂时增多。

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Abstract

T cells are key mediators of alloresponse during liver transplantation (LTx). However, the dynamics of donor-reactive T-cell clones in peripheral blood during a clinical T-cell-mediated rejection (TCMR) episode remain unknown. Here, we collected serial peripheral blood mononuclear cell samples spanning from pre-LTx to 1 year after LTx and available biopsies during the TCMR episodes from 26 rejecting patients, and serial peripheral blood mononuclear cell samples were collected from 96 nonrejectors. Immunophenotypic and repertoire analyses were integrated on T cells from rejectors, and they were longitudinally compared to nonrejected patients. Donor-reactive T-cell clone was identified and tracked by cross-matching with the mappable donor-reactive T-cell receptor repertoire of each donor-recipient pair in 9 rejectors and 5 nonrejectors. Before transplantation, the naive T-cell percentage and T-cell receptor repertoire diversity of rejectors was comparable to that of healthy control, but it was reduced in nonrejectors. After transplantation, the naïve T-cell percentages decreased, and T-cell receptor repertoires were skewed in rejectors; the phenomenon was not observed in nonrejectors. Alloreactive clones increased in proportion in the peripheral blood of rejectors before TCMR for weeks. The increase was accompanied by the naïve T-cell decline and memory T-cell increase and acquired an activated phenotype. Intragraft alloreactive clone tracking in pre-LTx and post-LTx peripheral blood mononuclear cell samples revealed that the pretransplant naïve T cells were significant contributors to the donor-reactive clones, and they temporarily increased in proportion and subsequently reduced in blood at the beginning of TCMR. Together, our findings offer an insight into the dynamic and origin of alloreactive T cells in clinical LTx TCMR cases and may facilitate disease prediction and management.

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