Laboratory of Molecular Biology and Immunology, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
Trends Immunol. 2023 Jul;44(7):542-550. doi: 10.1016/j.it.2023.05.005. Epub 2023 May 28.
The ability of T cells to undergo robust cell division in response to antigenic stimulation is essential for competent T cell function. However, this ability is reduced with aging and contributes to increased susceptibility to infectious diseases, cancers, and other diseases among older adults. To better understand T cell aging, improved measurements of age-related cellular changes in T cells are necessary. The recent development of machine learning (ML)-assisted transcriptome-based quantification of individual CD8 T cell age represents a significant step forward in this regard. It reveals both prominent and subtle changes in gene expression and points to potential functional alterations of CD8 T cells with aging. I argue that single-cell transcriptome-based age prediction in the immune system may have promising future applications.
T 细胞在抗原刺激下进行旺盛的细胞分裂的能力对于 T 细胞的功能至关重要。然而,这种能力随着年龄的增长而降低,导致老年人更容易感染传染病、癌症和其他疾病。为了更好地了解 T 细胞衰老,有必要对 T 细胞与年龄相关的细胞变化进行更好的测量。最近,机器学习(ML)辅助的基于转录组的个体 CD8 T 细胞年龄定量方法的发展,在这方面是一个重大的进步。它揭示了基因表达中的显著和微妙变化,并指出了 CD8 T 细胞衰老时潜在的功能改变。我认为,基于单细胞转录组的免疫系统年龄预测可能有很有前途的应用前景。