In a groundbreaking study published in the February 2026 issue of Aging-US, researchers have unveiled a sophisticated single-cell transcriptomic clock that sheds unprecedented light on the interplay of immune aging in the contexts of COVID-19 and HIV. This innovative approach, developed by Alan Tomusiak, Sierra Lore, and Eric Verdin along with their colleagues at the Buck Institute for Research on Aging, the University of Southern California, and the University of Copenhagen, advances the field by precisely measuring age-related molecular changes within discrete immune cell subsets.
Traditionally, studies of immune aging have relied on bulk analyses of mixed cell populations, obscuring the nuanced molecular mechanisms that underlie age-associated immune decline. Bulk measurements fail to distinguish whether aging signatures are driven by shifts in the proportions of different immune cells or by intrinsic aging processes inside individual cells. This limitation has hampered efforts to precisely characterize immune aging and its impact on disease susceptibility and progression.
To overcome this barrier, the authors harnessed the power of single-cell RNA sequencing (scRNA-seq), profiling nearly two million peripheral blood immune cells from healthy individuals across a broad age spectrum. They developed a novel computational framework named T immune cell transcriptomic clock (Tictock), which integrates automated classification of canonical T cell subsets with robust, cell-specific age prediction models. This hybrid model enables decomposition of systemic aging effects, reflected as changes in cell type frequencies, from intrinsic cellular aging measured at the transcriptomic level within each immune cell type.
Tictock was rigorously validated using both internal datasets and an external cohort from a recent study by Yasumizu et al. (2024), demonstrating high accuracy in cell type classification and age prediction, with F1 scores reaching 0.97 within the training dataset and 0.80 in external validation. This analytic rigor affirms the tool’s robustness and generalizability across independent datasets and experimental conditions.
Applying Tictock to samples from patients with acute SARS-CoV-2 infection revealed two salient immune aging effects. Firstly, COVID-19 infection significantly altered the composition of T cell subpopulations, particularly causing marked depletion of naïve CD4 and CD8 T cells, critical players in adaptive immune responses. Secondly, more striking was the acceleration of biological aging signatures specifically within naïve CD8 T cells, suggesting that viral infection instigates rapid intrinsic immune senescence beyond mere compositional shifts.
Contrastingly, in people living with HIV under long-term antiretroviral therapy, overall T cell proportions remained comparatively stable, indicating effective suppression of viral replication and immune system preservation. Nonetheless, naïve CD8 T cells in this group exhibited transcriptomic signatures indicative of premature aging, underscoring persistent immune dysregulation and cellular senescence despite clinical viral control.
Extensive gene ontology analyses of the genes driving age predictions across six distinct T cell clock models uncovered common biological pathways implicated in immune aging. Many of these genes encoded components of the cytosolic small ribosomal subunit and other ribosomal proteins, highlighting the importance of ribosome biogenesis and protein synthesis in the aging process. These findings complement growing evidence that dysregulation in translational machinery and proteostasis are hallmarks of cellular senescence and systemic aging.
Additionally, the study observed that older T cells exhibited shorter average transcript lengths, a molecular feature that may reflect altered RNA processing or stability associated with aging. This observation aligns with prior research linking transcript shortening to genomic and epigenomic changes in senescent cells, potentially affecting gene regulatory networks and immune function.
Tictock’s design to focus on relative intrinsic aging within discrete T cell subsets, rather than a generic overall biological age, represents a paradigm shift in immunogerontology. By disentangling systemic effects from cell-intrinsic molecular aging, this tool affords a refined resolution to monitor immune vulnerability, resilience, and the impact of chronic infections or inflammatory states on immune cell senescence.
The implications of this study are profound for clinical and research applications. Tictock could serve as a precise biomarker platform for immune risk assessment, enabling early detection of age-related immune dysfunction and stratification of patients according to their immune biological age. This capability is especially pertinent for monitoring long COVID syndrome, HIV reservoirs, and other conditions where immune aging drives morbidity.
Furthermore, understanding the molecular underpinnings of immune aging facilitates the identification of novel therapeutic targets aimed at restoring ribosomal function or modulating RNA metabolism to reinvigorate aged immune cells. The convergence of single-cell transcriptomics and advanced computational modeling epitomized by Tictock opens new avenues for interventions to delay immunosenescence and improve healthspan in virus-affected populations.
As an open-access publication, this research invites collaboration and validation across translational immunology laboratories globally, accelerating the integration of transcriptomic clocks into personalized medicine frameworks. The robust methodology employed underscores the essential role of cutting-edge bioinformatics in unraveling complex biological processes like aging.
Overall, this pioneering study not only enhances our mechanistic understanding of immune aging in infectious settings but also provides a scalable and reproducible analytic tool. Tictock exemplifies how leveraging single-cell technologies can revolutionize our capacity to measure and ultimately modulate the aging immune system at an unprecedented resolution.
Subject of Research: Cells
Article Title: Single-cell transcriptomics reveal intrinsic and systemic T cell aging in COVID-19 and HIV
News Publication Date: 8-Feb-2026
Web References: http://dx.doi.org/10.18632/aging.206353
Image Credits: Copyright © 2026 Tomusiak et al., distributed under CC BY 4.0
Keywords: aging, transcriptomic clock, aging biomarkers, systemic aging, intrinsic aging
Tags: age-related immune decline at single-cell levelaging biomarkers in T cellscomputational framework for aging clocksimmune aging molecular mechanismsimmune cell subset aging profilesprecision aging measurement in infectious diseasessingle-cell RNA sequencing immune cellssingle-cell transcriptomic clock for immune agingsystemic T cell aging in HIVT cell aging in COVID-19Tictock immune cell classificationtranscriptomic analysis of peripheral blood
