Abstract

Biomarkers of aging offer insights into how diseases and interventions affect biological systems. However, most current biomarkers are based on bulk cell measurements, making it difficult to distinguish between changes driven by shifts in cell type composition (systemic effects) versus intrinsic changes within individual cells. To address this, we used single-cell RNA sequencing to analyze aging-related changes at both the cellular and bulk levels. We developed Tictock (T immune cell transcriptomic clock), a single-cell transcriptomic clock capable of predicting age and cell type across six human T cell subsets. Applying Tictock, we found that acute COVID-19 is associated with increased proportions of CD8+ cytotoxic T cells, whereas T cell composition remains stable in people with HIV on antiretroviral therapy (HIV+ART). Both COVID-19 and HIV+ART are linked to an increase in transcriptomic age, specifically within naïve CD8+ T cells. Gene Ontology enrichment of 209 genes shared across six clock models identified common pathways including the cytosolic small ribosomal subunit, TNF receptor binding, and cytosolic ribosome components. A correlation was also observed between aging and mean transcript length. These findings underscore the promise of single-cell transcriptomic biomarkers to disentangle the systemic and cell-intrinsic components of immune aging and to measure immune aging.