Transcriptome-based measurement of CD8+ T cell age and its applications

• Published in: Trends in immunology 2023-07, Vol.44 (7), p.542-550
• Main Author: Weng, Nan-ping
• Format: Article
• Language: English
• Subjects: Aged; Aging; CD8-Positive T-Lymphocytes; Cellular Senescence - physiology; DNA methylation; Humans; Immune System; machine learning; somatic mutation; T cell aging; telomere; Transcriptome
• ISSN: 1471-4906; 1471-4981; 1471-4981
• DOI: 10.1016/j.it.2023.05.005

T cell aging has a profound impact on cell-mediated immunity.Measuring the age of T cells is a crucial step towards understanding the functional impact of aging on T cells.Transcriptome-based and ML-assisted age-prediction models can offer a precise method for measuring individual CD8+ T cell aging with functional implications.Estimating the age of individual CD8+ T cells provides a useful tool for gaining a better understanding of CD8+ T cell aging and for potential clinical applications. To gain a deeper understanding of CD8+ T cell aging, accurate measurements of cellular age are crucial. One promising approach is an ML-based age-prediction algorithm that uses transcriptomic data to provide estimates of CD8+ T cell age. By capturing differences in the status of cell differentiation and the history of cell divisions, this algorithm assigns different ages to CD8+ T cells. This may enable researchers to better evaluate the functional impact of age on individual cytotoxic CD8+ T cells. 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.