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移植肾后,激活的 T 细胞可导致高危排斥状态,进而导致肾移植失败。

T Cells With Activated Drive the High-Risk Rejection State to Renal Allograft Failure After Kidney Transplantation.

机构信息

Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-sen University, Guangzhou, China.

Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.

出版信息

Front Immunol. 2022 Jul 1;13:895762. doi: 10.3389/fimmu.2022.895762. eCollection 2022.

DOI:10.3389/fimmu.2022.895762
PMID:35844542
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9283858/
Abstract

In kidney transplantation, deteriorated progression of rejection is considered to be a leading course of postoperative mortality. However, the conventional histologic diagnosis is limited in reading the rejection status at the molecular level, thereby triggering mismatched pathogenesis with clinical phenotypes. Here, by applying uniform manifold approximation and projection and Leiden algorithms to 2,611 publicly available microarray datasets of renal transplantation, we uncovered six rejection states with corresponding signature genes and revealed a high-risk (HR) state that was essential in promoting allograft loss. By identifying cell populations from single-cell RNA sequencing data that were associated with the six rejection states, we identified a T-cell population to be the pathogenesis-triggering cells associated with the HR rejection state. Additionally, by constructing gene regulatory networks, we identified that activated , as a core transcription factor that was regulated by in T cells, was closely linked to poor allograft function and prognosis. Taken together, our study provides a novel strategy to help with the precise diagnosis of kidney allograft rejection progression, which is powerful in investigating the underlying molecular pathogenesis, and therefore, for further clinical intervention.

摘要

在肾移植中,排斥反应的恶化被认为是术后死亡的主要原因。然而,传统的组织学诊断在读取分子水平的排斥状态方面存在局限性,从而导致与临床表型不匹配的发病机制。在这里,我们通过应用一致流形逼近和投影以及莱顿算法对 2611 个公开的肾移植微阵列数据集进行分析,发现了六种具有相应特征基因的排斥状态,并揭示了一种高风险(HR)状态,该状态对于促进同种异体移植物丢失至关重要。通过从单细胞 RNA 测序数据中识别与六种排斥状态相关的细胞群体,我们鉴定了与 HR 排斥状态相关的 T 细胞群体作为引发发病机制的细胞。此外,通过构建基因调控网络,我们发现激活作为受 T 细胞中调控的核心转录因子,与同种异体移植物功能不良和预后密切相关。综上所述,我们的研究提供了一种新的策略,有助于对肾移植排斥反应进展进行精确诊断,这对于研究潜在的分子发病机制具有强大的作用,从而为进一步的临床干预提供了依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/f05517ecb224/fimmu-13-895762-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/dc0187050a3d/fimmu-13-895762-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/c99e6ad366c2/fimmu-13-895762-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/5398c05c991e/fimmu-13-895762-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/773402a54281/fimmu-13-895762-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/f05517ecb224/fimmu-13-895762-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/dc0187050a3d/fimmu-13-895762-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/c99e6ad366c2/fimmu-13-895762-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/5398c05c991e/fimmu-13-895762-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/773402a54281/fimmu-13-895762-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6d0/9283858/f05517ecb224/fimmu-13-895762-g005.jpg

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Sci Rep. 2021 Dec 10;11(1):23815. doi: 10.1038/s41598-021-03115-z.
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The Impact of Inflammation on the Immune Responses to Transplantation: Tolerance or Rejection?炎症对移植免疫反应的影响:耐受还是排斥?
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