衰老过程中血液免疫细胞的综合单细胞图谱。

IF 4.1 Q2 GERIATRICS & GERONTOLOGY npj aging Pub Date : 2024-11-29 DOI:10.1038/s41514-024-00185-x
Igor Filippov, Leif Schauser, Pärt Peterson
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引用次数: 0

摘要

单细胞技术的最新进展促进了免疫系统中与年龄相关的变化的研究。然而,先前的研究通常使用不同的标记基因来注释免疫细胞群,这使得比较结果具有挑战性。在这项研究中,我们结合了七个单细胞转录组数据集,包括来自103个供体的100多万个细胞,以创建来自年轻人和老年人的人类外周血单核细胞(PBMC)的统一图谱。使用一组一致的免疫细胞标记基因注释,我们标准化了免疫细胞的分类,并评估了它们在两个年龄组中的流行程度。整合的数据集揭示了几个与衰老相关的一致趋势,包括CD8+幼稚T细胞和MAIT细胞的下降以及非经典单核细胞室的扩张。然而,我们在其他细胞类型中观察到显著的变异性。我们对长链非编码RNA MALAT1hi T细胞群的分析表明,该群体是高度异质性的,是naïve-like和记忆样细胞的混合物。尽管在比较不同年龄组的基因表达时,数据集之间存在很大差异,但我们确定了CD8+幼稚T细胞衰老的高可信度特征,其标志是促炎基因的表达增加。总之,我们的研究强调了标准化现有单细胞数据集的重要性,以便能够跨多个数据集全面检查与年龄相关的细胞变化。
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An integrated single-cell atlas of blood immune cells in aging.

Recent advances in single-cell technologies have facilitated studies on age-related alterations in the immune system. However, previous studies have often employed different marker genes to annotate immune cell populations, making it challenging to compare results. In this study, we combined seven single-cell transcriptomic datasets, comprising more than a million cells from one hundred and three donors, to create a unified atlas of human peripheral blood mononuclear cells (PBMC) from both young and old individuals. Using a consistent set of marker genes for immune cell annotation, we standardized the classification of immune cells and assessed their prevalence in both age groups. The integrated dataset revealed several consistent trends related to aging, including a decline in CD8+ naive T cells and MAIT cells and an expansion of non-classical monocyte compartments. However, we observed significant variability in other cell types. Our analysis of the long non-coding RNA MALAT1hi T cell population, previously implicated in age-related T cell exhaustion, showed that this population is highly heterogeneous with a mixture of naïve-like and memory-like cells. Despite substantial variation among the datasets when comparing gene expression between age groups, we identified a high-confidence signature of CD8+ naive T cell aging marked by an increased expression of pro-inflammatory genes. In conclusion, our study emphasizes the importance of standardizing existing single-cell datasets to enable the comprehensive examination of age-related cellular changes across multiple datasets.

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