Research ArticleImmunologyPulmonology
Open Access | 10.1172/jci.insight.185061
1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Address correspondence to: Anuradha Ray, 3459 Fifth Ave, MUH NW628, Pittsburgh, Pennsylvania, 15213, USA. Phone: 412.802.3191; Email: raya@pitt.edu.
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Address correspondence to: Anuradha Ray, 3459 Fifth Ave, MUH NW628, Pittsburgh, Pennsylvania, 15213, USA. Phone: 412.802.3191; Email: raya@pitt.edu.
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
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5Center for Biological Imaging,
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7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Address correspondence to: Anuradha Ray, 3459 Fifth Ave, MUH NW628, Pittsburgh, Pennsylvania, 15213, USA. Phone: 412.802.3191; Email: raya@pitt.edu.
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Address correspondence to: Anuradha Ray, 3459 Fifth Ave, MUH NW628, Pittsburgh, Pennsylvania, 15213, USA. Phone: 412.802.3191; Email: raya@pitt.edu.
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Address correspondence to: Anuradha Ray, 3459 Fifth Ave, MUH NW628, Pittsburgh, Pennsylvania, 15213, USA. Phone: 412.802.3191; Email: raya@pitt.edu.
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
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5Center for Biological Imaging,
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7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
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3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
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7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
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2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
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5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
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7Center for Systems Immunology, and
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4Department of Cell Biology,
5Center for Biological Imaging,
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7Center for Systems Immunology, and
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
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2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
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1Department of Medicine, Division of Pulmonary, Allergy and Critical Care Medicine,
2Asthma and Environmental Lung Health Institute at UPMC,
3Department of Immunology,
4Department of Cell Biology,
5Center for Biological Imaging,
6Department of Pediatrics,
7Center for Systems Immunology, and
8Department of Environmental and Occupational Health, University of Pittsburgh, Pittsburgh, Pennsylvania.
Address correspondence to: Anuradha Ray, 3459 Fifth Ave, MUH NW628, Pittsburgh, Pennsylvania, 15213, USA. Phone: 412.802.3191; Email: raya@pitt.edu.
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Published March 6, 2025 - More info
Published in Volume 10, Issue 8 on April 22, 2025Aberrant immune response is a hallmark of asthma, with 5%–10% of patients suffering from severe disease exhibiting poor response to standard treatment. A better understanding of the immune responses contributing to disease heterogeneity is critical for improving asthma management. T cells are major players in the orchestration of asthma, in both mild and severe disease, but it is unclear whether specific T cell subsets influence asthma symptom duration. Here we show a significant association of airway CD8+ effector memory T cells re-expressing CD45RA (TEMRAs), but not CD8+CD45RO+ or tissue-resident memory T cells, with asthma duration in patients with severe asthma (SA) but not mild to moderate asthma (MMA). Higher frequencies of IFN-γ+CD8+ TEMRAs compared with IFN-γ+CD45RO+ T cells were detected in SA airways, and the TEMRAs from patients with SA but not MMA proliferated ex vivo, although both expressed cellular senescence-associated biomarkers. Prompted by the transcriptomic profile of SA CD8+ TEMRAs and proliferative response to IL-15, airway IL15 expression was higher in patients with SA compared with MMA. Additionally, IL15 expression in asthmatic airways negatively correlated with lung function. Our findings add what we believe is a new dimension to understanding asthma heterogeneity, identifying IL-15 as a potential target for treatment.
Graphical AbstractAsthma is a chronic heterogeneous disease of the airways affecting more than 300 million people worldwide and is clinically characterized by variable respiratory symptoms and reversible airflow limitation on pulmonary function testing (1–4). The vast majority of patients have mild to moderate asthma (MMA) but an estimated 5%–10% have a clinical diagnosis of severe asthma (SA) (1, 2, 4–7). Disease symptoms in patients with SA are characteristically poorly managed by the current standard of care, inhaled corticosteroids (CS), even when used at high doses or accompanied by oral CS (2, 4, 6, 7).
Since the early 1990s, immunophenotyping of asthma in humans and animal models has established an important role of Th2/type 2 (T2) cells as mediators of asthma pathogenesis, in both MMA and SA (2, 7–9). However, use of more advanced tools to study immune cells at the single-cell level in combination with machine learning showed activation of additional immune pathways that include type 1 (T1) T cells, and in some patients, also Th17 cells, in the setting of more severe disease (6, 10–13). These pathways are unaffected by T2-directed biologics and recalcitrant to CS, identifying an unmet need for new avenues for managing disease in these patients.
T lymphocytes in chronic age-associated illnesses are known to acquire highly differentiated phenotypes and become senescent, defined as cells in permanent cell-cycle arrest (14). While replicative senescence is typically associated with old age (15, 16), there is increasing appreciation for stress-induced premature senescence in lung diseases such as idiopathic pulmonary fibrosis and chronic obstructive pulmonary disease (17, 18). The senescent phenotype is hypothesized to exist to prevent the progeny of damaged cells from undergoing malignant conversion, yet senescent cells, including T cells, can be highly inflammatory, acquiring a senescence-associated secretory phenotype (SASP), when the cells secrete a range of biomolecules, including proinflammatory cytokines, such as IFN-γ and TNF-α, chemokines, matrix-associated metalloproteinases, and bioactive lipids, among others (19–22). Multiple memory T cell subsets infiltrate the airways of asthmatics, as we and others have shown (6, 12), which begs the question whether one or more of these cell types associate with the time since the onset of asthma symptoms. One subset of memory T cells, effector memory T cells re-expressing CD45RA (TEMRAs), are terminally differentiated T cells that lose cell surface expression of CD27, CD28, and CD127 but regain expression of CD45RA, the latter typically expressed by naive T cells (23, 24). Both CD4+ and CD8+ TEMRAs have been described in humans but these cells are not present in mice. TEMRAs have been associated with multiple chronic inflammatory diseases that include autoimmune disease (25) and Alzheimer disease (26). While TEMRA abundance is commonly associated with chronological age (15), the blood, spleen, and lung are particularly prone to harboring CD8+ TEMRAs regardless of age (24). Emerging literature emphasizes roles for persistent viral infections and inflammatory disease conditions as drivers of TEMRAs, especially CD8+ TEMRAs, with the cells showing features of cellular senescence (15, 27, 28). Although the inflammatory characteristics of CD8+ TEMRAs should enable their clearance by the immune system, evidence suggests that age, persistent viral infections, and disease-associated immune dysfunction can cause their accumulation (15, 27, 28). A consequence of the increased numbers of senescent CD8+ TEMRAs with enhanced innate-like functions, typically associated with natural killer (NK) cells (29), is induction of chronic sterile inflammation that impairs tissue homeostasis and causes tissue damage, a state collectively termed inflammaging (15, 30).
Our earlier studies of immune and molecular mechanisms of SA involving analysis of airway transcriptomic data (31, 32), airway immune cells in humans and in mouse models (10, 33–36), and more recent studies of bronchoalveolar lavage (BAL) and airway epithelial cells utilizing advanced bioinformatic tools (6, 11) highlight the presence of an increased T1/IFN-γ immune response in a subset of these patients who poorly respond to CS. This T1hi steroid-resistant phenotype has been also appreciated by others in both adults (12, 37) and children (38, 39). Notably, the combined presence of T1 and T2 immune responses appears to be a hallmark of the sickest of asthma patients (31, 35, 37), with IFN-γ or the T1 phenotype negatively associating with airway obstruction, as measured by the percentage of predicted forced expiratory volume in 1 second (FEV1), a measure of lung function (10, 40). Because of the association of TEMRAs with viral infections, which are features of steroid-resistant SA in both children (38) and adults (37), and their propensity for IFN-γ secretion, TEMRAs are also a potential source of IFN-γ in SA in addition to effector/memory and tissue-resident memory (TRM) T cells (6, 10, 33, 35).
Here, we examined TEMRAs in patients with a diagnosis of asthma. We found an increase in the percentage of CD8+, but not CD4+, TEMRAs in the peripheral blood (PB) and BAL cells of patients with SA, but not MMA, positively correlating with asthma symptom duration. Compared with other memory T cells in patients with SA, the percentages of cells expressing IFN-γ and senescence-associated biomarkers were higher in CD8+ TEMRAs. Patients with SA were found to have higher airway expression of IL15, encoding a known TEMRA activator and chemokine for CD8+ T cells (41, 42). IL15 expression positively correlated with expression of T cell–associated genes and IFNG but negatively correlated with lung function. However, as opposed to canonical descriptions of TEMRAs and senescence, CD8+ TEMRAs were more proliferative in patients with SA than MMA in response to T cell receptor (TCR) stimulation and IL-15, suggesting a potential mechanism for immunopathology in SA.
ResultsCD8+ TEMRAs are detectable in PB and BAL cells in patients with asthma. PB mononuclear cells (PBMCs) from patients with MMA or SA were stained with a high-dimensional flow cytometry panel of antibodies and analyzed in combination with clinical metadata obtained from the Immune Mechanisms in Severe Asthma (IMSA) study (see Methods). These data were paired with previously generated mass cytometry (CyTOF) data (Figure 1A) (6) from BAL cells that were manually reanalyzed to investigate T cell subsets. Demographic and clinical characteristics of donors can be found in Supplemental Table 1; supplemental material available online with this article; https://doi.org/10.1172/jci.insight.185061DS1 Using a gating strategy that accounted for the differences in T cell subsets in PB and BAL cells (Supplemental Figure 1), we measured the prevalence of CD4+ and CD8+ TEMRAs in these 2 compartments in patients with MMA and SA.
Association of T cell subsets with time since the onset of asthma symptoms. (A) Overall experimental design. (B) Linear regression of PB CD8+ TEMRAs (percentage of CD8+ cells) as a function of the time in years since the onset of an individual’s asthma symptoms. (C) Linear regression of PB (left) and BAL (right) CD8+ TEMRAs (percentage of CD8+ cells) from patients with MMA as a function of the time in years since the onset of an individual’s asthma symptoms. (D) Linear regression of PB (left) and BAL (right) CD8+ TEMRAs (percentage of CD8+ cells) from patients with SA as a function of the time in years since the onset of a subject’s asthma symptoms. (E) Linear regression of PB (left) and BAL (right) CD8+CD45RO+ memory (percentage of CD8+ cells) from patients with SA as a function of the time in years since the onset of a subject’s asthma symptoms. (F) Linear regression of PB CD8+ TEMRAs (percentage of CD8+ cells) as a function of BAL CD8+ TEMRAs (percentage of CD8+ cells). Statistical significance in B–F determined using Spearman’s nonparametric correlations, with solid black lines representing simple linear regression line and shaded blue area representing 95% confidence interval.
CD4+ TEMRAs were low in abundance in both PB and BAL and were therefore not examined further. Based on the association of TEMRAs with age, we hypothesized that CD8+ TEMRAs would increase in frequency with age but discovered no relationship between the percentage of CD8+ TEMRAs in PB or BAL and donor age. However, we found a positive correlation between percentage CD8+ TEMRAs in the CD8+ T cell compartment and the time since the onset of asthma symptoms in both the PB and BAL (Figure 1B) after combining all asthma patients (n = 32). When examined by asthma severity, this trend was not observed in percentage CD8+ TEMRAs from patients with MMA in either compartment (Figure 1C), but in patients with SA, there was a positive association with CD8+ TEMRAs in PB that reached statistical significance in BAL (Figure 1D). Interestingly, there was no association between the time since the onset of asthma symptoms and CD8+CD45RO+ memory T cells (a composite of effector memory T cells and central memory T cells) in PB and there was a significant negative association with these cells in BAL (Figure 1E) among patients with SA. These trends remained when evaluating all patients with asthma (MMA and SA combined) (Supplemental Figure 2A). We previously reported the presence of CD8+ TRM T cells in the airways of patients with SA (6). However, we did not detect any association between CD8+ TRMs and the time since onset of symptoms in patients with either MMA or SA (Supplemental Figure 2B).
Taken together, these data suggested that CD8+ TEMRAs increasingly comprise more of the CD8+ compartment in patients with SA, but not MMA, the longer the individual has had asthma. We found a significant positive relationship between CD8+ TEMRAs in PB and BAL in all patients with asthma (Figure 1F), suggesting that TEMRAs accumulate at similar rates in BAL and PB and that circulating PB CD8+ TEMRAs may reflect BAL CD8+ TEMRA biology. This is in accordance with prior studies demonstrating the presence of CD8+ TEMRAs in the lung and PB (24).
PB CD8+ TEMRAs in patients with SA express T1 cytokines and show senescent features. CD8+ TEMRAs in other chronic illnesses have been described as senescent, hyperinflammatory, and terminally differentiated (26, 42–45). These cells express a marker of naive T cells, CD45RA, yet do not retain other hallmarks of naive T cells and are skewed toward T1 cytokine secretion (42, 43, 45). We therefore hypothesized that PB CD8+ TEMRAs would be similar to TEMRAs in other human illnesses, would express biomarkers associated with senescence at higher rates in patients with SA, and would exhibit a SASP with more IFN-γ expression. To address this, we measured intracellular expression of cytokines canonically associated with T1, T2, and T17 immune programs. Whether in PB (Figure 2A) or BAL cells (Figure 2B), very low percentages of CD8+ TEMRAs or CD45RO+ T cells expressing either IL-4 or IL-17 were detected. However, a significantly higher percentage of CD8+ TEMRAs expressed IFN-γ when compared with CD8+CD45RO+ memory T cells, especially in the BAL (Figure 2B). We did not detect a significant difference between IFN-γ+CD8+ TEMRAs and IFN-γ+CD8+CD45RO+ memory T cells in the BAL cells of patients with MMA (Supplemental Figure 2C). We therefore gated on the IFN-γ+ cell subset in T cells from patients with SA for further analysis and found lower percentages of CD8+ TEMRAs with markers of activation, including CD27 and CD28 when compared with other subsets (Figure 2C), consistent with prior TEMRA descriptions (26, 43). Lower percentages of CD8+ TEMRAs expressed IL-2R (CD25) and IL-7R (CD127) than CD8+CD45RO+ memory T cells (Figure 2C). In addition, a smaller percentage of PB CD8+IFN-γ+ TEMRAs in SA expressed PD-1 when compared with CD8+IFN-γ+CD45RO+ memory T cells, showing they did not display complete or intermediate levels of exhaustion (46), and a significantly higher percentage expressed a biomarker of senescence, CD57 (Figure 2D) (29). Compared with CD8+IFN-γ+CD45RO+ T cells, higher percentages of CD8+IFN-γ+ TEMRAs expressed other senescence-associated markers such as killer cell lectin-like G1 (KLRG1) (29) and adhesion G protein–coupled receptor 56 (GPR56) (Figure 2D) (47). Notably, expression of these biomarkers of T cell senescence was also detected in the PB of CD8+IFN-γ+ TEMRAs in patients with MMA (Supplemental Figure 2D).
Compared with CD8+CD45RO+ memory T cells, CD8+ TEMRAs in PB display higher percentages of IFN-γ+ and senescence marker–expressing cells. (A) Percentage of cytokine-expressing PB cells from patients with SA. (B) Percentages of BAL cells expressing cytokines from patients with SA. (C and D) Percentages of PB IFN-γ+ cells expressing senescence-associated surface proteins from patients with SA. Statistical significance for data in A, B, and D determined using Wilcoxon’s matched-pairs signed rank test and for data in C determined using Kruskal-Wallis followed by multiple pairwise comparisons. Data represent median ± 95% confidence interval.
These data supported our hypothesis that CD8+ TEMRAs in patients with SA recapitulate the hyperinflammatory, senescent phenotype that has been documented in other chronic inflammatory states in humans such as organ transplantation (42), chronic infection (28), and autoimmune disease (25). To the best of our knowledge, CD8+ TEMRAs have not been described in asthma previously and yet could be a significant source of T1 cytokines in subsets of patients with SA.
PB CD8+ TEMRAs show significant transcriptional divergence from CD8+CD45RO+ memory T cells. To further explore CD8+ TEMRAs in patients, we performed bulk RNA sequencing (RNA-seq) on sorted PB CD8+ TEMRAs, CD8+CD45RO+ memory, and CD8+ naive T cells isolated from 3 patients with SA (Figure 3A). Cells were not stimulated with anti-TCR or phorbol myristate acetate with ionomycin prior to cell sorting. We examined the number of differentially expressed genes (DEGs), both upregulated and downregulated, in SA CD8+ TEMRAs compared to SA naive CD8+ T cells that were non-overlapping when a similar comparison was made between the transcriptomes of SA CD8+CD45RO+ T cells and SA naive CD8+ T cells. When compared with CD8+ naive T cells, CD8+ TEMRAs differentially upregulated 289 genes and differentially downregulated 718 genes that were not shared with CD8+CD45RO+ memory T cells (Figure 3B). These results, combined with earlier biomarker and cytokine experiments, suggested that CD8+ TEMRAs are differentially programmed from other canonical memory T cell populations in SA. We analyzed the data further to identify specific DEGs and biological pathways in CD8+ TEMRAs compared to the other 2 cell types. As shown in Figure 3C, lower expression of the gene SIRPG in CD8+ TEMRAs compared with CD8+CD45RO+ T cells was observed. This may lower the threshold of TEMRA activation in SA given that a single nucleotide polymorphism in this gene was previously associated with increased CD8+ effector T cell activity with promotion of autoimmunity (48). CD8+ TEMRAs differentially downregulated IL7R (CD127) and CD27 (Figure 3C) that was also evident at the protein level (Figure 2C). Although IL-7 is critical for the maintenance of naive and memory T cells (49, 50), TEMRAs may be less dependent on IL-7 for their maintenance. Instead, differential upregulation of IL2RB in CD8+ TEMRAs compared with CD8+ naive T cells (Figure 3D) suggested that these cells are wired to respond to both IL-2 and IL-15, as IL-2Rβ is a shared signaling subunit for both of these cytokines in the induction of T cell proliferation (51, 52). As such, compared with CD4+ T cells, a higher pool of IL-2R in CD8+ T cells was reported in a study that also demonstrated greater CD8+ T cell proliferation in response to IL-2 (53). Whereas canonical CD8+ effector memory T cells sustain their antiviral effects through either IL-2 or IL-15, we found that CD8+ TEMRAs differentially upregulated CD38 compared with CD8+CD45RO+ T cells (Figure 3C), which may dampen their antiviral activity, increased CD38 expression having been previously shown to reduce cytotoxic functions of CD8+ T cells against viral infection in patients with lupus (54). However, increased expression of HIPK2, associated with type I IFN–mediated antiviral responses (55), may offset higher CD38 expression in the TEMRAs. IL-15 is known to maintain basal proliferation of memory CD8+ T cells (56, 57). Downregulation of TCF7 (which encodes the transcription factor TCF-1), observed in CD8+ TEMRAs, was also previously associated with CD57+ cells, a feature of cellular senescence (Figure 3D) (58). Finally, when compared with CD8+ naive T cells, CD8+ TEMRAs also differentially upregulated SPON2, which encodes the extracellular matrix protein spondin 2. SPON2 gene expres
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