- Research Article
- 10.1016/j.intimp.2026.116476
The iterative shrinkage thresholding algorithm reveals dynamic aging trajectories of human T lymphocytes via multidimensional spectral flow cytometry analysis.
- Mar 14, 2026
- International immunopharmacology
- Yan Chen + 18 more +18
Immunosenescence is a fundamental hallmark of aging, characterized by differential susceptibility across immune cell lineages. T lymphocytes are particularly vulnerable; however, the distribution and dynamics of aging-associated immune markers across T cell subsets remain incompletely characterized. In this study, we enrolled 462 healthy individuals stratified into six groups spanning 20 to over 70years. Using multiparametric spectral flow cytometry, we systematically characterized T lymphocyte subsets, capturing both immunophenotypic diversity and functional status. We identified a progressive age-associated decline in the frequencies of CD8+, γδ+, and Vδ2+ T cells, alongside an increase in CD4+ T cells. Aging was marked by the reduction of naive T cells and an expansion of terminally differentiated effector memory populations. Among all subsets, CD8+ T cells exhibited the greatest sensitivity to age-associated immunophenotypic remodeling, characterized by reduced expression of CD27 and CD28, and increased expression of senescence-associated surface markers including CD57 and KLRG1, together with elevated cytotoxic effector molecules including IFN-γ and granzyme B. Using these parameters, we defined 10 immune biomarkers through machine learning approaches that accurately predicted chronological age (R2=0.81, P<0.001). We further reconstructed the trajectory of T cell aging using ISTA-based sparse coding, which can capture aging-related immunophenotypic patterns in over 80% of individuals across age groups. Together, these findings demonstrate the dynamic remodeling of T lymphocytes across the human lifespan and provide a foundation for immune age modeling and risk stratification for unhealthy aging.
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