美国圣路易斯华盛顿大学Maxim N. Artyomov课题组发现，人类T细胞的多维特征分析显示高水平的CD38表达，标志着近期胸腺迁出细胞和与年龄相关的初始T细胞重塑。2024年9月24日，《免疫》杂志在线发表了这项成果。

研究人员对单细胞RNA测序/ATAC测序数据的分析通过SOX4、IKZF2、TOX和CD38蛋白的表达区分了近期胸腺迁出（RTE），其中表面CD38^hi的表达普遍标识了CD8⁺和CD4⁺ RTE。

研究人员进一步确定了158个个体队列中RTE和成熟细胞的动态，包括与年龄相关的转录重编程和细胞因子产生的变化。光谱细胞计数分析揭示了初始CD8⁺和CD4⁺ T细胞普遍存在的两个衰老轴：（1）CD38⁺⁺细胞（RTE）减少和（2）CXCR3^hi细胞增加。识别RTE使得胸腺健康的直接评估成为可能。此外，解析初始T细胞重塑的动态有助于了解老年人对疫苗接种和感染的反应能力。

据了解，胸腺萎缩是人类免疫衰老的一个关键因素，导致胸腺输出减少以及循环中RTE初始T细胞的下降。目前，关于人类RTE的精确定义及其相应的细胞表面标记仍不清晰。

附：英文原文

Title: Multidimensional profiling of human T cells reveals high CD38 expression, marking recent thymic emigrants and age-related naive T cell remodeling

Author: Pavla Bohacova, Marina Terekhova, Petr Tsurinov, Riley Mullins, Kamila Husarcikova, Irina Shchukina, Alina Ulezko Antonova, Barbora Echalar, Jan Kossl, Adam Saidu, Thomas Francis, Chelsea Mannie, Laura Arthur, Stephen D.R. Harridge, Daniel Kreisel, Philip A. Mudd, Angela M. Taylor, Coleen A. McNamara, Marina Cella, Sidharth V. Puram, Theo van den Broek, Femke van Wijk, Pirooz Eghtesady, Maxim N. Artyomov

Issue&Volume: 2024-09-24

Abstract: Thymic involution is a key factor in human immune aging, leading to reduced thymic output and a decline in recent thymic emigrant (RTE) naive T cells in circulation. Currently, the precise definition of human RTEs and their corresponding cell surface markers lacks clarity. Analysis of single-cell RNA-seq/ATAC-seq data distinguished RTEs by the expression of SOX4, IKZF2, and TOX and CD38 protein, whereby surface CD38hi expression universally identified CD8+ and CD4+ RTEs. We further determined the dynamics of RTEs and mature cells in a cohort of 158 individuals, including age-associated transcriptional reprogramming and shifts in cytokine production. Spectral cytometry profiling revealed two axes of aging common to naive CD8+ and CD4+ T cells: (1) a decrease in CD38++ cells (RTEs) and (2) an increase in CXCR3hi cells. Identification of RTEs enables direct assessment of thymic health. Furthermore, resolving the dynamics of naive T cell remodeling yields insight into vaccination and infection responsiveness throughout aging.

DOI: 10.1016/j.immuni.2024.08.019

Source: https://www.cell.com/immunity/abstract/S1074-7613(24)00418-7