General and individualized changes in T cell immunity during aging

Abstract

Functional alterations with age are observed in all human systems, but the aging of the adaptive immune system displays both general changes affecting all individuals, and idiosyncratic changes that are unique to individuals. In the T cell compartment, general aging manifests in three ways: (1) the reduction of naïve T cells, (2) the accumulation of differentiated memory T cells, and (3) a reduced overall T cell receptor (TCR) repertoire. Idiosyncratic impacts of aging, such as changes in the TCR repertoires of altered memory and naïve T cells are shaped by each person’s life exposures. Recent advancements in single-cell sequencing provide new information including the identification of new subpopulations of T cells, characteristics of transcriptome changes in T cells and their TCR clonotype with age, and measurement of individual cell age. Here, we focus on the changes in T cell subpopulations, transcriptomes and TCR repertoires in overall and antigen-specific T cell population with aging.

The general changes of T cell compartment over a human lifetime

The T cell compartment is composed of approximately 4 × 10¹¹ T cells in an adult human, comprising both naïve T cells and various subpopulations of memory T cells distributed in the blood circulatory and lymphatic systems as well as lymphoid and non-lymphoid tissues.^1,2 The constant interactions between the host and the environment result in continuous changes and adaptations in the T cell compartment throughout an individual's lifetime. Hallmarks of age-related changes in the T cell population include a decrease in naïve T cells due to diminished thymic production after puberty,^3,4 and the accumulation of differentiated memory T cells.^5,6 Additionally, age-related changes in the T cell microenvironment combined with cumulative lifetime challenges further contribute to molecular and cellular changes within T cells at all stages of differentiation. Collectively, these changes impact the ability of T cells to respond to pathogens and cancerous cells in older adults.

Another fundamental change in T cells with age is the alteration of the T cell receptor (TCR) repertoire, which comprises a vast array of different TCRs capable of recognizing a wide range of potential antigens and pathogens. The reduction in TCR repertoire size and the expansion of selective TCR clones with age are well documented.^7–9 Due to individual differences in TCR repertoire contents and varied lifetime antigenic experiences, the composition of the aged TCR repertoire is highly individualized, leading to individually distinct consequences. Although older adults generally possess a reduced TCR repertoire, each older adult has a uniquely reduced or enriched set of specific TCRs that differ from others. This heterogeneous nature of the TCR repertoire in older populations presents an urgent challenge in understanding T cell aging. A better understanding of both general age-related changes in T cells and their specific TCR repertoires in each older adult will facilitate more tailored clinical approaches for diagnosis and treatment in the rapidly expanding older population.

Recent applications of deep sequencing-based methods, such as single-cell RNA sequencing (scRNAseq),¹⁰ single-cell¹¹ and bulk-cell TCR sequencing,¹² and combing with other single-cell omics including scATACseq¹³ and CITEseq¹⁴ have significantly increased the resolution of age-related changes in T cells. These methods not only identify novel T cell subpopulations that exhibit substantial changes with age but also document transcriptional changes with age using distinct patterns that can be only observed at the single-cell resolution. Combined with high-dimensional flow cytometry, CyTOF¹⁵ and tetramer methods,¹⁶ it has become feasible for the first time to understand T cell immunity and its changes at a single-cell level with defined antigen specificity and determined TCR clonotype. In the following, we will discuss recent advances in the understanding of the changes in T cell composition, transcriptome and TCR repertoire with age.

Age-associated changes in T cell subpopulations and transcriptomes

Recent scRNAseq analyses have not only enhanced the resolution of age-associated changes in subpopulations of CD4⁺ and CD8⁺ T cells but also have revealed distinct transcriptome changes within these defined subpopulations of T cells. Here we summarize age-associated changes in CD4⁺ and CD8⁺ T cells at single cell resolution (Fig. 1).

Figure 1.

Age-associated changes in subpopulations of T cells and gene expressions. (A) Age-associated increase in T cell subpopulations: (1) Cytotoxic CD4⁺ T cells;^17,20 (2) Inflammatory Tregs (Regulatory T Cells),^21,72 and (3) GZMK⁺ CD8⁺ memory T cells.³⁷ (B) Patterns of age-associated gene expression changes: (1) Change in the number of gene-expressing cells; an increase or decrease in the population of cells expressing specific genes; (2) Change in gene expression level in individual cells: variation in the amount of gene expression per cell; and (3) Change by both number of gene-expressing cells and expression level: Concurrent changes in both the number of cells expressing specific genes and the expression level within each cell.³⁵ These graphs were generated using BioRender.

CD4⁺ T cells

Application of scRNAseq analysis has revealed a new age-associated subpopulation of CD4⁺ T cells: cytotoxic CD4⁺ T cells.^17–19 Cytotoxic CD4⁺ T cells from aged mice express high levels of Eomes and produce Tnf-α, Ifn-γ, granzyme B, and perforin upon in vitro stimulation.¹⁷ In humans, cytotoxic CD4⁺ T cells express the chemokine receptor CXCR3 and are recruited by keratinocyte-secreted chemokine CXCL9 to the skin, where they eliminate cytomegalovirus glycoprotein B-positive senescent fibroblasts in an MHC II-dependent manner.²⁰ Cytotoxic CD4⁺ T cells have also been reported to significantly increase in supercentenarians, exhibiting a transcriptional program similar to that of CD8⁺ T cells, likely due to substantial clonal expansion..¹⁸ These findings illustrate the plasticity of T cell differentiation with aging and how the CD4⁺ T cells adapt to age- and environment-related changes to maintain essential cytotoxic functions of T cells.

Regulatory T cells (Tregs) play a crucial role in modulating the immune response, and changes in their function with age directly affect susceptibility to autoimmune diseases, as well as the outcomes of infections and cancer. Studies have shown that Tregs accumulate in aged individuals.^21,22 However, it remains unclear whether this accumulation enhances Treg function or merely compensates for a decline in the functional capacity of individual Treg cells with age..^23,24 Several recent studies have examined transcriptional and epigenetic changes occurring in Tregs of aged mice and humans using single-cell genome and epigenetics sequencing.^21,24–27 Tregs from the lungs of aged mice express high levels of Tbet and RORyt, and their target genes (IFN-γ and IL-17) post-infection due to loss of DNA methylation in these genes.²⁶ Subpopulation analysis by scRNAseq of mouse Treg shows 6 subpopulations: cluster 1 significantly increased with age while cluster 3 decreases with age.²⁷ Interestingly, cluster 1 exhibited downregulation of Il27ra and Prkch, both of which are crucial for maintaining Treg function. Furthermore, cluster 1 may consist of resting Tregs, characterized by increased expression of Sell and Cpt1a, and effector Tregs, marked by the upregulation of Icos. In contrast, cluster 3 expressed cytotoxic molecules such as granzyme A and B. However, the significance of the decline of cytotoxic molecule expressed by Treg cells with age in overall Treg function requires further study.

Aging also impacts the differentiation and distribution of other CD4⁺ T cell subsets, including Th1, Th2, Th17, and Th9, with different patterns of CD4⁺ T cell subpopulation distribution observed in different tissues with aging.^17,28–32 For example, Yin et al. show that Th1 and Th2-like CD4⁺ effector memory cells are increased in muscle, and Th17 cells accumulate in bones of older humans.²⁸ Furthermore, these Th1, Th2-like T_EM in muscle and Th17 in bone had increased NFκB regulated transcription and enhanced pro-inflammatory gene signatures.²⁸ Conversely, another single-cell atlas study on human PBMCs showed that Th2 CD4⁺ memory T cells and HLA-DR⁺ CD4⁺ memory T cells accumulated more in the blood of aged humans and that pathways related to TCA cycles were enriched in old naïve CD4⁺ and CD8⁺ T cells.³¹ The enriched TCA cycles could associate with increased reactive oxygen species (ROS) production in dysfunctional mitochondria as it has been found that several steps in TCA cycles could produce ROS.³³

While the number of nave CD4⁺ T cells is not significantly reduced with aging, the age-associated transcriptional remodeling has been identified in naïve CD4⁺ T cells from older adults.³⁴ Aging-associated HELIOS deficiency in naive CD4⁺ T cells alter chromatin remodeling and promotes effector cell responses.¹⁴ Two major changes in gene set enrichment analysis in old naïve CD4⁺ T cells have been found: metabolic modifications and active cytokine signaling. Elevated IL-2/STAT-5 signaling pathway and higher expression of CD25 in aged naïve CD4⁺ T cells may contribute to enhanced homeostatic proliferation. Aging-associated HELIOS deficiency in naive CD4⁺ T cells alter chromatin remodeling and promotes effector cell responses.¹⁴ Similarly, another study discovers that naïve CD4⁺ T cells from older adults have altered transcription factor profiles upon in vitro stimulation, with enhanced expression of BATF and IRF4, and reduced expression of ID3 and BCL6, favoring Th9 differentiation.³² Collectively, age-associated changes in CD4⁺ T cells include increased cytotoxic subset and altered Treg function. Further research is needed to clarify the underlying mechanisms and the precise functional consequences of these changes.

CD8⁺ T cells

scRNAseq analysis of human and mouse CD8⁺ T cells has revealed novel subpopulations and insights into gene expression changes with age.^35–37 An analysis of ∼120,000 individual CD8⁺ T cells from 2 healthy human cohorts identified 10 subpopulations of CD8⁺ T cells and their shared and distinct age-related changes in gene expression.³⁵ The shared gene expression changes across naïve and different memory subsets suggest underlying mechanisms of CD8⁺ T cell aging that are independent of differentiation status. Interestingly, the analysis of gene expression changes with age at the single-cell level reveals three distinct patterns that are not detectable when the analysis is conducted at the bulk cell level: (1) a change in the number of gene-expressing cells in the sample, (2) a change in the gene expression level of each cell, and (3) both changes in the number of gene-expressing cells and the expression level within each cell. Among the 3 patterns of change, changes in only the number of gene-expressing cells accounted for approximately 50% of genes, changes by both number and expression level accounted for approximately 25% of genes, and changes in expression level alone accounted for approximately 20% of genes. These patterns of change appear gene-specific and are associated with unique cellular functions based on the GSEA analysis. Further understanding these different transcriptional controls in the number of expressing cells and expression levels within cells with age in CD8⁺ T cells will provide mechanistic insights of aging impact on immune function.

Several reports show an age-associated accumulation of GZMK⁺ CD8⁺ T cells in mice and humans, which accounts for 20% of CD8⁺ T_EM and T_CM cells in young adults and around 40% in older adults.^37–41 GZMK⁺ CD8⁺ T cells are pro-inflammatory with an exhausted-like phenotype, characterized by high expression of PD-1, LAG3, and Tox, and are positively associated with elevated plasma levels of inflammatory cytokines (IL-6, TNF-α, and IL-8).⁴¹ These cells increase in both lymphoid and non-lymphoid tissues in aged mice and humans and exhibit significant clonal expansion with age. Functionally, initial reports suggest that GZMK⁺ CD8⁺ T cells can secrete granzyme K to induce senescence signals in aged fibroblasts.⁴¹ Other studies indicate that GZMK⁺ CD8⁺ T cells may directly suppress functional CD8⁺ T cell responses due to their high expression of inhibitory molecules. Reducing the number of GZMK⁺ CD8⁺ T cells led to an improved CD8⁺ T cell response to viral infections in aged mice.

Another study by Luo et al., reported that healthy older adults had more CD8⁺ T_CM cells while frail old adults had more CD4⁺ T_CM than young adults.⁴² The balance between CD4⁺ T_CM and CD8⁺ T_CM may be key in maintaining immune system function in healthy aging. Within CD4⁺ or CD8⁺ T_CM or T_EM cells, there is higher transcriptome variability as age increases and from healthy to frail condition. In addition, naïve T cells from older adults had upregulated gene expressions involved in Toll-like receptor and MAPK signaling pathways, whereas naïve T cells from frail adults were enriched activated genes in viral responses and apoptosis.⁴² These scRNA-seq analyses reveal novel age-related subsets, such as GZMK⁺ CD8⁺ T cells, as well as common transcriptome changes across different differentiated CD8⁺ T subsets. However, due to the limited cohort sizes in current studies and the remarkable heterogeneity of human CD8⁺ T cells and their age-related changes,¹³ further research involving larger cohorts with longitudinal follow-up samples is necessary.

Quantification of cellular age based on transcriptomic changes

Altered gene expression is a hallmark of T cell aging.^41,43 These age-associated changes in gene expression provide a foundation for understanding shifts in T cell function in older adults. With recent advancements in single-cell RNA sequencing, age-related gene expression can now be analyzed across the entire transcriptome at the individual cell level. This offers valuable insights, not only into functional changes but also for more accurate quantification of cellular aging.

Machine learning (ML) is a data-analytical technique that processes multi-dimensional datasets to generate predictive models of biological outcomes.⁴⁴ By learning from cellular data derived from donors of varying chronological ages, ML models can predict cellular age based on transcriptomic features.⁴⁵ At the single-cell transcriptome level, an ML model has been developed that accurately predicts the age of individual CD8⁺ T cells.³⁵ Remarkably, the predicted age of 90% of total CD8⁺ T cells from all donors aligns within 10 to 14 years of their chronological age, suggesting that the majority of CD8⁺ T cells were generated before puberty.

Mechanistically, predicted cell ages indicate that naïve CD8⁺ T cells are younger than memory cells, a finding corroborated by other biological measurements, such as telomere length⁴⁶ and recent thymic production.⁴⁷ The predicted age also correlates positively with the number of somatic mutations in individual cells, consistent with well-documented age-related cellular changes due to cumulative cell division and responses to DNA damage.⁴⁸ This ML model has been applied to clinical scenarios, including the quantification of naïve CD8⁺ T cell aging in human immunodeficiency virus type 1 (HIV-1) infection and the monitoring of CAR T cell expansion in vivo. It is anticipated that ML models for age prediction, based on single-cell transcriptomes from various T cell types, will provide precise quantification of T cell age under a range of clinical conditions in the future.

TCR repertoire changes in T cell subpopulations with age

The TCR and its collection of different members within an individual have fascinated immunologists for decades, but its enormous size posed significant technical challenges. Recent applications of deep sequencing methods have rapidly expanded TCR repertoire analysis. Human TCR repertoire studies have employed a small number of T cells (ranging 0.1 to 10 × 10⁶) T cells and applied various methods to estimate a projected size of the TCR repertoire.⁴⁹ The current TCR repertoire information is primarily based on the analysis of TCRβ sequences of T cells.^50–52 Single cell αβ paired TCR analysis is still lagging due to its high cost and small number of cells per assay. There are two common measurements of the TCR repertoire: (1) the total number of TCR clonotypes (species richness)⁵³ and (2) diversity indices (Shannon entropy and Simpson index) measuring TCR clonal distribution and expansion.^54,55 Experimental based analysis suggests that the lower bound predicted human TCR repertoire size is around 10.^8.8,9,56,57 In additional, the content of the TCR repertoire is highly individualized,^9,58 influenced by genetic differences in major histocompatibility complex (MHC) polymorphism, selected by the available antigenic epitopes, and by the available TCR clonotypes among humans.⁵⁹ Initial studies of blood T cells from cross-sectional cohorts show a relatively linear reduction of TCRβ repertoire size with age from newborns to centenarians^60,61 (Fig. 2).

Figure 2.

Age-associated changes in general and antigen-specific TCR repertoire. (A) Changes in general TCR repertoire with age: (1) Reduced species richness: predominantly observed in naïve T cells and (2) Increased clonal expansion mostly in memory T cells: Primarily seen in memory T cells.^8,9 (B) Alterations in antigen-specific TCR repertoire.⁷⁰ CD8⁺ T cells recognizing influenza A virus (IAV) M1_58-66 epitope show age-associated changes: CD8⁺ T cells recognizing this epitope from Children/Adults possess public TCR clonotypes and exhibit robust activation-induced proliferation. In contrast, CD8⁺ T cells recognizing this epitope from older adults are mostly characterized by private TCRs with reduced proliferative capacity. These graphs were generated using BioRender.

General TCR repertoire in CD4⁺ T cells

Qi et al. analyzed TCRβ sequences between young and old human adults and found that the reduction of the naive CD4⁺ T cell repertoire is more prominent than that of the memory CD4⁺ T cell repertoire with age.⁸ Yoshida et al. analyzed the CDR3β repertoire of total CD4⁺ T cells using longitudinal follow-up samples from six adults aged 23 to 65 years, with 3 visits spanning 20 years. Their findings confirmed a decrease in TCRβ repertoire size and an increase in clonal expansion in human CD4⁺ T cells with age.⁶²

More recently, Sun et al. conducted a parallel analysis of TCRα and TCRβ sequences from naive and memory CD4⁺ T cells in a longitudinal cohort of 30 adults, aged from their late 20s to early 80s at the first visit, with an average follow-up of 9.2 years.⁹ Utilizing a modified UMI-based RNAseq method,¹² which reduces PCR and sequencing-associated errors, they projected TCR repertoire richness based on the actual circulating T cell number of each donor. This study presented two interesting findings: (1) A significant reduction in the richness of the TCRβ repertoire, but not in the TCRα repertoire of CD4⁺ T cells, with age and (2) a significant reduction in TCRβ repertoire richness in naive but not in memory CD4⁺ T cells, providing evidence of distinct changes in TCR repertoire richness with age in naive and memory CD4⁺ T cells. Clonal analysis of these longitudinal samples revealed that (1) TCRα and TCRβ sequences are increasingly retained with age and (2) the retention of TCRα and TCRβ sequences is more pronounced in memory T cells compared to naive T cells. These findings suggest that the age-related reduction in TCR repertoire size contributes to an increasingly stable TCR repertoire.⁹ The evolving dynamics of TCR repertoire richness in naive versus memory CD4⁺ T cells with age and how these changes impact immune system resilience and adaptation over time require much further investigations.

General TCR repertoire in CD8⁺ T cells

The TCR repertoire size of CD8⁺ T cells is smaller than that of CD4⁺ T cells.^8,9,57 Similar age-associated reduction of richness and diversity index are reported, but the degree of age-associated changes is more profound in CD8⁺ T cells. This is evidenced by the more rapid reduction in TCR richness in naïve CD8⁺ T cells (TCRα = −2.2%/year and TCRβ = −3.5%/year) compared to naïve CD4⁺ T cells (TCRα = −0.7%/year and TCRβ =−2.3%/year). Furthermore, increased clonal expansion of TCRβ repertoire of naïve CD8⁺ T cells is more pronounced than in naive CD4⁺ T cells.⁹ Like CD4⁺ T cells, the TCRβ repertoire richness does not significantly change in memory CD8⁺ T cells with age. These findings demonstrate that age leads to a more profound reduction in richness of TCRα and TCRβ repertoires in naïve CD8⁺ T cells than naïve CD4⁺ T cells. The rapid loss of TCR repertoire in naïve CD8⁺ T cells would reduce the cytotoxic functions of T cells and an increase in clonally expanded cytotoxic CD4⁺ T cells may represent an adaptive change of T cell immunity in the healthy super older adults.¹⁸

The longevity of TCRs in an individual over time is influenced by the frequency of their antigenic encounters. When analyzing public TCR sequences shared among different individuals, Sun et al. found that the frequency of public TCRα and TCRβ sequences in total TCRs increased with age in both CD4⁺ and CD8⁺ T cells, although this increase was only significant in CD8⁺ T cells without their pairing information.⁹ Since the donors have different MHC genotypes, it remains to be determined whether the increasing share of public TCRs is a result of shared antigenic experience or other factors. Nevertheless, characterizing unique and shared TCR sequences and determining their antigenic specificity in older adults will enhance our understanding of T cell immunity, with clear clinical implications.

In summary, general TCR repertoire analyses, primarily focused on the TCRβ repertoire, show age-associated alterations, including reduced richness and increased clonal expansion, particularly in CD8⁺ T cells. However, there is an urgent need for αβ paired TCR repertoire analysis, which will require further innovations in methods to handle significantly larger sample sizes at an affordable cost. This new information will provide deeper insights into the complexity of the human αβ TCR repertoire and its precise changes with age.

Antigen-specific T cell changes with age: individualized cause and consequence

The application of MHC class I and II tetramer technology in high-dimensional flow cytometry has enabled the identification and isolation of antigen-recognizing CD8⁺ and CD4⁺ T cells. However, the current knowledge of antigen specific TCR repertoire come from mainly analysis of CD8⁺ T cells as MHC class I tetramers have been more widely used for determination of TCR specificity. The MHC tetramer technology combined with scRNAseq and scTCRseq methods, it becomes feasible to analyze the differentiation status and TCR clonotypes of defined antigen specificity at individual cell resolution.⁶³ The diversity of the TCR repertoire among antigen-specific, differently differentiated T cells and how it changes with age remain unknown. Additionally, the extent to which the antigen-specific TCR repertoire is uniquely influenced by individual’s past antigenic encounters and environmental factors within a population is undetermined. Some recent studies following antigen-specific T cells post-COVID-19 infection and vaccination offer a glimpse into how antigen-specific T cell responses and their potential changes with age may occur.

Clonal expansion of CMV-specific CD8⁺ T cells based on TCRβ sequences, but not αβ paired TCRs, has been reported.^64–66 Luo et al. demonstrated the presence of αβ paired TCR clones specific for CMV and other pathogens in their single-cell TCR sequence dataset.⁴² Although only a few dozen αβ paired TCR clonotypes matched previously reported CMV specific TCR clonotypes, these clones were abundant and found exclusively in older adults, suggesting their clonal expansion in vivo over time. Furthermore, these CMV-specific CD8⁺ T cells were all memory, not naïve, CD8⁺ T cells, consistent with their past antigen experience.⁴² The findings provide an initial glimpse into the differentiation status and TCR clonotypes of CMV-specific CD8⁺ T cells at single-cell resolution. Given the limited number of donors in each group, further studies with larger cohorts and longitudinal follow-up are needed to confirm these findings. Such research will provide new insights into the in vivo dynamics of antigen-specific T cells over time.

Reports of CD8⁺ TCRβ repertoire specific for an epitope of influenza A virus (IAV) Matrix protein M1 (M1_58–66) show a reduction in the frequency of cells recognizing this epitope with age, possibly with enhanced cross-reactivity,^67,68 and an increase in private CD8⁺ TCRs in older adults.⁶⁹ van de Sandt et al., reports a single cell paired TCR analysis of M1_58-66 in newborn, children, adult and older adult and show a reduction in proliferation ability of these T cells in response to in vitro antigenic challenge in older adults compared to children and adults, along with reduced expressions of cytotoxic molecules.⁷⁰ Analysis of TCR repertoires of M1-specfic CD8⁺ T cells show a dynamic change throughout different age groups: newborns have a highly diverse TCR repertoire, children and adults have greatly clustered TCRs, and older adults have again diversified TCR repertoire. However, the TCRs from the children/adults group are mostly public TCRs, while TCRs from older adults are mostly private TCRs. Furthermore, the robust proliferative response of these M1-specific CD8⁺ T cells is associated with public TCRs, in contrast to the reduced proliferative response of M1-specific CD8⁺ T cells from the older adults with private TCRs. The authors further demonstrate that the private TCRs from older adults display a reduced ability to recognize variant peptides of M1, explaining their lower binding capacity, avidity, functionality and proliferating capacity compared to the public TCRs found in children/adults. These findings suggest that a lifetime experience with IAV alters predominantly public TCR clonotypes in children and adults to the more private TCRs with lower proliferative response to M1 and its variants. Preserving public TCR diversity or reducing TCR “privatization” with age will be the ultimate challenge.

Choy et al. analyzed the CD8⁺ T cell response against a dominant nucleocapsid epitope (N_222-230, LLLDRNQL, or LLL) of SARS-CoV-2 in COVID-19 convalescent patients.⁷¹ Although COVID-19 disproportionately affects older adults, they did not find any significant age-related differences in the frequencies of total and subset CD8⁺ T cells (T_N, T_CM, T_SCM, T_EM, and T_EMRA) specific for LLL epitope, nor in the activation-induced expansion of CD8⁺ T cells. One possible explanation is that the older convalescent adults in the study presented only mild symptoms of COVID-19, which may not reflect the immune status of the general elderly population. The authors then investigated whether there were differences that could explain the variability between expanders and non-expanders of LLL-recognizing CD8⁺ T cells when stimulated in vitro. By comparing the transcriptomes of LLL tetramer⁺ CD8⁺ T cells between expanders and non-expanders using GSEA, they found that CD8⁺ T cells from expanders expressed genes involved in the negative regulation of chemotaxis and cytokine activity, whereas CD8⁺ T cells from non-expanders had enriched genes involved in chromatin modification, histone binding, and regulation of the innate immune response. Further analysis of TCR quality between the two groups was conducted using a machine learning model to select comparable TCRs. When LLL tetramer⁺ CD8⁺ T cells were selected based on high LLL-binding TCR scores, the GSEA conducted with these selected LLL tetramer⁺ CD8⁺ T cells yielded similar findings. These results suggest that these underlying mechanisms may regulate activation-induced proliferation and expansion of LLL tetramer⁺ CD8⁺ T cells.

Efforts to combine antigen specificity, TCR clonotype, and differentiation status at single-cell resolution have produced rich and exciting results. However, while the number of antigens and associated TCRs studied remains limited, much more work is needed to fully understand the scope and diversity of antigen-specific TCRs, their cross-reactivity, and how changes with aging impact specific T cell functions.

Conclusion

Our understanding of T cell immunity and its changes with age has greatly advanced with recent single-cell technologies, allowing for the first time the characterization of TCR clonotypes, differentiation, and aging status at single-cell resolution. The identification and analysis of antigen-specific CD4⁺ and CD8⁺ T cells, along with tracking changes in their frequency and TCR clonotype over time in a longitudinal manner, will offer unprecedented insights into the composition of antigen-specific T cells, their differentiation status, and evolution over a lifetime, reflecting the history of the dynamic interactions between antigenic challenges and T cell experience.

Individual older adults experience a shared decline in overall T cell function, but they also exhibit specific strengths and weaknesses for certain pathogens/antigens due to altered cellular functionality and availability of competent TCRs, or both. By gaining insights into these general and individual changes, particularly identifying individual susceptibility to specific pathogens, it becomes possible to develop targeted interventions to enhance both general and antigen-specific T cell responses. Thus, single-cell omics analysis, including TCR clonotype determination, specificity and affinity assessment, holds great promise for advancing our understanding of aging T cell immunity and improving T cell functions in infection, vaccination, and other conditions in older adults.

Funding

This work was supported entirely by the Intramural Research Programs of the NIH, National Institute on Aging.

Conflicts of interest

The authors declare no conflict of interests.