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巨细胞病毒重塑衰老过程中的淋巴免疫:一个具有预测模型的单细胞图谱

CMV reshapes lymphoid immunity in aging: a single-cell atlas with predictive modeling.

作者信息

Grabauskas Titas, Verschoor Chris P, Trinity Luke, Marches Radu, Thibodeau Asa, Nehar-Belaid Djamel, Eryilmaz Giray, Picard Emilie, Kuo Chia-Ling, Schmader Kenneth E, Colon-Emeric Cathleen, Whitson Heather E, Paust Silke, García-Sastre Adolfo, Banchereau Jacques, Kuchel George A, Ucar Duygu

机构信息

The Jackson Laboratory for Genomic Medicine; Farmington, CT 06030, USA.

University of Connecticut School of Medicine; Farmington, CT 06030, USA.

出版信息

bioRxiv. 2025 Jun 27:2025.06.24.661167. doi: 10.1101/2025.06.24.661167.

DOI:10.1101/2025.06.24.661167
PMID:40666903
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12262386/
Abstract

Cytomegalovirus (CMV), a common herpesvirus, establishes lifelong latency and increases in prevalence with age; yet its systemic impact on the aging immune system remains incompletely understood. We profiled circulating immune cells from healthy older adults (median age: 73) who were CMV(+) or CMV(-) using single-cell RNA-sequencing and validated key findings by flow cytometry. CMV(+) individuals exhibited significant expansion of adaptive immune cells: CD4 and CD8 TEMRA T, GZMK CD8 T, γδ T, and atypical B cells. Among innate immune cells, monocytes and dendritic cells remained largely unchanged while (adaptive) NK cells increased and CD56 NK cells decreased. To facilitate CMV assessment in datasets with unknown CM serostatus, we developed , a machine learning classifier that accurately predicts CMV serostatus from single-cell data across platforms and age groups (97% accuracy). These findings reveal extensive CMV-associated immune remodeling in older adults and underscore the importance of incorporating CMV status in studies of immune aging.

摘要

巨细胞病毒(CMV)是一种常见的疱疹病毒,会建立终身潜伏感染,且患病率随年龄增长而上升;然而,其对衰老免疫系统的全身性影响仍未完全明确。我们使用单细胞RNA测序对健康老年成年人(中位年龄:73岁)中CMV阳性或阴性个体的循环免疫细胞进行了分析,并通过流式细胞术验证了关键发现。CMV阳性个体表现出适应性免疫细胞的显著扩增:CD4和CD8 TEMRA T细胞、GZMK CD8 T细胞、γδ T细胞和非典型B细胞。在固有免疫细胞中,单核细胞和树突状细胞基本保持不变,而(适应性)自然杀伤细胞增加,CD56自然杀伤细胞减少。为便于在CM血清状态未知的数据集中评估CMV,我们开发了一种机器学习分类器,可根据跨平台和年龄组的单细胞数据准确预测CMV血清状态(准确率97%)。这些发现揭示了老年人中广泛的CMV相关免疫重塑,并强调了在免疫衰老研究中纳入CMV状态的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/071bd8cb5c2c/nihpp-2025.06.24.661167v1-f0005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/00de87c74099/nihpp-2025.06.24.661167v1-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/243145c7dbc9/nihpp-2025.06.24.661167v1-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/33370ab25422/nihpp-2025.06.24.661167v1-f0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/1515f273649e/nihpp-2025.06.24.661167v1-f0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/43ab330b8784/nihpp-2025.06.24.661167v1-f0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/9cc8a91dc366/nihpp-2025.06.24.661167v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/d3dd1de198f6/nihpp-2025.06.24.661167v1-f0002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a52/12262386/071bd8cb5c2c/nihpp-2025.06.24.661167v1-f0005.jpg

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