Prolonged T-cell activation and long COVID symptoms independently associate with severe COVID-19 at 3 months

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    This valuable paper uses a cohort of SARS-CoV-2 infected people to link immune signatures 3 months post-infection with persistent, long COVID-19 symptoms. The strength of the evidence presented is solid based on a wide array of immunologic assays and a strategically designed cohort, with some claims that are incomplete based on a lack of specifically designed endpoints, lack of analysis of regulatory signals, and incomplete use of control samples. A couple of findings are novel and will be of interest to clinicians and immunologists, particularly that degree of inflammation at 3 months does not impair the generation of SARS-CoV-2 humoral and cellular memory responses and that cellular immune signatures are only somewhat correlated with long COVID-19 symptoms.

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Abstract

Coronavirus disease-19 (COVID-19) causes immune perturbations which may persist long term, and patients frequently report ongoing symptoms for months after recovery. We assessed immune activation at 3–12 months post hospital admission in 187 samples from 63 patients with mild, moderate, or severe disease and investigated whether it associates with long COVID. At 3 months, patients with severe disease displayed persistent activation of CD4 + and CD8 + T-cells, based on expression of HLA-DR, CD38, Ki67, and granzyme B, and elevated plasma levels of interleukin-4 (IL-4), IL-7, IL-17, and tumor necrosis factor-alpha (TNF-α) compared to mild and/or moderate patients. Plasma from severe patients at 3 months caused T-cells from healthy donors to upregulate IL-15Rα, suggesting that plasma factors in severe patients may increase T-cell responsiveness to IL-15-driven bystander activation. Patients with severe disease reported a higher number of long COVID symptoms which did not however correlate with cellular immune activation/pro-inflammatory cytokines after adjusting for age, sex, and disease severity. Our data suggests that long COVID and persistent immune activation may correlate independently with severe disease.

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  1. Author Response

    Reviewer #1 (Public Review):

    In this study, authors examine immune signatures from patients that experienced mild, moderate, or severe COVID-19 symptoms and followed them for months to evaluate whether there was a correlation between their immune activation phenotypes, disease severity, and long COVID. Authors observed higher T cell activation/proliferation marker expression in blood samples of patients with severe disease whereas other cell types were more or less unchanged. The authors also examined the cytokine profile of the patient's serum samples to determine the potential drivers of T cell activation phenotypes. Authors then perform T-cell responses to viral peptides to determine the differences in activation phenotypes with disease severity.

    The major strengths of the paper appear in the evaluation of the appropriate cohort of human samples and following them over a period of months. Additionally, the authors perform detailed T-cell analysis in an unbiased way to determine any possible activation correlations with disease severity. The authors also perform antigen-specific T-cell analysis via peptide stimulation which adds to the overall findings. However, there are a number of drawbacks that need to be mentioned. Firstly, the phenotypes of T cells prior to the 3-month time-point are not known. Hence, there is no information on baseline or during the early phase of infection. Secondly, the response is largely obtained from blood. How much information about T cells in blood correlate with lung disease is a matter of concern. Analysis of lungs, where actual disease manifestation is ideal, however close to impossible in the human cohort. Alternatively, analysis of local lymph node aspirate or nasal swabs could be useful. Thirdly, the claim that bystander T cell activation plays a role seems loose, specifically the IL-15 in vitro data. Moreover, the analysis of T cells seems very focused on activation/proliferation phenotypes. Alternative T cell phenotypes such as regulatory, IL-10 producing, or FoxP3 expression are not extensively analyzed.

    Major points

    1. In Figure 1, the CD4 T cell activation phenotypes do not seem consistent across the groups. Why does moderate vs. severe show increases in CXCR3 expression but not mild vs. severe? The same goes for other markers. Performing T cell stimulation with class II peptides specific for CoV-2 and looking at IFN etc. to determine antigen-specific T cells and then gating on these activation/proliferation markers may be a better way to observe differences.

    Figure 1 shows activation phenotypes of total CD4+ T-cells. We performed similar analysis on SARS-C0V-2 spike-specific CD4+ T cells as suggested by Reviewer 1 (using 15-mer peptides overlapping by 10 amino acids which are able to stimulate both CD4+ and CD8+ T cells- see Figure 5), but we did not observe differences between the groups (data not shown). Importantly, as reported in the discussion (page 18 from “Our data does not support the persistence of SARS-CoV-2 antigens at 3 months….”) we did not observe significant activation of spike-specific CD4+ or CD8+ T cells which suggests that T cell activation in these patients at 3 months is not driven by persistence of SARS-CoV-2 spike antigens.

    1. One major drawback is the control patients. It would have helped to include a batch of samples from uninfected patients. Or to have the plasma/blood from patients before COVID-19 symptoms. This way there is a baseline for each group that could be compared. It is difficult to draw broad conclusions across the group at 3 months if we do not know their baseline phenotypes.

    We did not have access to blood samples from these patients prior to COVID-19 infection. However, we have now added an analysis of matched samples from the same patients at 12 months post infection (N=33, see Figure 2- figure supplement 1 and also response to Reviewer 2). These data show a significant decrease in T cell activation at 12 months compared to 3 months. T cell activation has decreased to largely undetectable “baseline” levels at 12 months, that are similar between patients who had experienced mild, moderate or severe COVID-19. This lack of T cell activation at 12 months likely reflects the T cell profiles that patients will have had prior to COVID-19 infection.

    1. Although the authors focused on activating/proliferating markers to correlate with disease severity, this analysis does not consider alternate T cell phenotypes such as the ones with regulatory or anti-inflammatory phenotypes. Did authors detect differences in T cells with regulatory profiles such as expression of IL-10, FoxP3, etc. in their unsupervised UMAP analysis or otherwise flow experiments?

    Due to limited blood volumes we were unable to analyse regulatory/anti-inflammatory T cells phenotypes. Our serum cytokine data does not suggest statistically significant differences in serum IL-10 levels in patients with mild, moderate or severe disease. However, it is possible that we may have missed differences in FoxP3+ regulatory or IL-10- producing T cells.

    Reviewer #2 (Public Review):

    The manuscript is well written, the data are based on well-performed experiments, and the conclusions are supported by the data. The authors study thoroughly the global phenotype of T and NK cells and also analyze antigen-specific T cell frequencies. The data confirm that individuals who had severe COVID-19 disease (required ventilation and/or ITU admission) have slightly more activated CD4 and CD8 T cells at 3 months post-infection and report more frequently long COVID symptoms, yet the novelty of this manuscript is to show that these two are not linked to each other. Moreover, the manuscript confirms that patients across all disease severities mount and maintain memory T cell and antibody responses to SARS-CoV-2.

    The authors find that patients who recovered from severe COVID-19 3 months ago have more activated CD4+ and CD8+ T cells than patients who recovered from the mild disease. Although the difference is significant, the frequency of CD4+ T cells with an activated phenotype is increased only by about 2-fold (~2% vs ~1%), while the frequency of activated CD8+ T cells is about 6% vs 4%, which should be added to the results to better describe the extent of the activation.

    As the authors mention in the discussion, it cannot be excluded that the more activated T cell phenotype in patients who recovered from severe COVID-19 is not rather a consequence of the increased comorbidities associated with this group. However, their Luminex analysis of the serum shows that the levels of cytokines TNF-a, IL-4, IL-12, IL-15, and IL-17A decline by 8 and 12 months, suggesting that the immune activation by 3 months is most likely a consequence of the previous severe viral infection.

    To strengthen this point, PBMC is probably not available at a later time point, to see if the increased T cell activation decreases in line with the serum cytokines. Yet, the authors should at least try to repeat the experiments of coculturing CD3+ T cells from healthy volunteers with the serum of mild/severe patients at 8-12 months post-recovery (Fig. 3 D-E).

    Thank you for these suggestions. We had access to PBMCs from N=33 matched patients at 12 months post admission and have now performed analyses of these samples. Our results show that CD4+ and CD8+ T cell activation at 12 months is significantly decreased compared to that observed at 3 months (Figure 2- figure supplement 1). We show that the frequencies of Ki67+ CD38+ CD4+ and CD8+ T cells are significantly decreased at 12 compared to the 3-month time point. Similarly, the frequencies of CXCR3+ CD4+ and CD8+ T cells are strongly decreased at 12 compared to 3 months post admission. Activated HLA-DR+ CD38+ and granzyme B+ CD8+ T cells are also significantly decreased from 3 to 12 months post admission. Unsupervised UMAP analyses shows that the cell distribution and density of CD4+ and CD8+ T cell populations was similar across all severity groups at 12 months post infection, while major differences are observed at 3 months between the patient groups (Figure 2- figure supplement 1 K). We added this information in the manuscript at page 9 (see tracked changes) and in Figure 2- figure supplement 1.

    Thank you for suggesting we repeat the co-culture experiments of healthy donor PBMCs with serum of mild and severe patients at 12 months post admission. We co-cultured healthy PBMCS from the same donors (only 3 out of the 4 donors used for the 3 months experiment were still accessible) with serum from mild and severe patients at 12 months. Notably, we observed that IL-15R upregulation did not occur upon co-culture of healthy donor PBMCs with plasma from severe patients at 12 months. This suggests that factors inducing IL-15R upregulation present in the 3 months plasma may be absent in the 12 month plasma. We have added this new data to the manuscript (Figure 3E)

    The authors tried to find if the activated T cell phenotype or increased serum cytokines at 3 months post-infection is linked with increased long COVID symptoms. The study does not find any direct association when the data are adjusted for age, sex, and severity. This is the only novelty of this study, yet it is an important piece of information in the attempt to broaden our understanding of the underlying causes of long COVID symptoms.

    Overall, it would be important to understand if increased frequencies of T cell activation (~2-fold) and increased levels of serum cytokines at 3 months following severe COVID-19 that resulted in ventilation and/or ITU admission is specific to severe SARS-CoV-2 infection, or if similar consequences are resulting also from other severe acute viral infections. Addressing this question is beyond the scope of the manuscript, yet it should be discussed.

    We agree this is an important question. In H7N9 influenza infection persistent T cell activation was associated with fatal disease while T cell activation early during infection associated with positive clinical outcomes (Wang et al. Nature Comms 2018). Aging is also known to alter T cell function and the persisting low-grade inflammation present in elderly individuals may also facilitate the persistence of bystander activated T cells (Yunis et al Trends in Microbiology 2023). We have added these considerations in the discussion (page 18-19).

    Reviewer #3 (Public Review):

    In this paper, the authors used a cohort study to link immune signatures in blood 30 days after COVID-19 infection as possible predictors of prolonged symptomatology. The paper partially achieves its aims. While the selected analyses are comprehensive, the cohort design is appropriate and the mechanistic ex vivo work is clever and convincing, the strength of conclusions is somewhat limited by the selection of imprecise clinical endpoints, and the lack of analyses examining T regulatory signatures.

    Strengths of the paper are:

    • The paper includes a comprehensive and structured immune analysis.

    • The paper is extremely clearly written.

    • The use of manual gating and unsupervised analysis in Fig 1 is complementary and helpful.

    • Bystander T cell experiments with IL-15 are useful and attempt to explore mechanisms from human samples which are traditionally very challenging.

    • The experiments shown in Figure 4 documenting equal Cov2 T cell responses in all 3 cohorts are an extremely important result.

    Major concerns are:

    • The significance of the study is somewhat limited by the small sample size.

    • The symptomatic outcome scale for PASC is blunt and poorly captures severity. More state-of-the-start scales of symptomatic severity and heterogeneity exist for PASC. I suggest this and other papers as an example: https://pubmed.ncbi.nlm.nih.gov/36454631/

    Thank you for this suggestion. Additional outcome measures have now been included in our analysis, refer to the results section and the updated Figure 6- source data 1 A-B.

    • The omission of analyses examining T regulatory functions is a missed opportunity and these may be impaired in this population.

    We have acknowledged this as a limitation of the study.

    • This is a challenging question that can be applied to many exploratory studies of this nature: how can we rule out the possibility that statistically significant differences in Figs 1, 2 & 3 are statistically significant but biologically meaningless? All cellular and cytokine measures of immune responses shown in these figures are not routinely measured in the clinic. Are there studies that can be cited to show that these differences are sufficient to have a causal impact on prolonged symptoms and tissue damage rather than just correlations with these outcomes?

    This is a challenging question, and we were unable to find studies correlating these measurements with tissue damage and prolonged symptoms. In our study we however suggest that prolonged T cell activation is not related to ongoing long-COVID symptoms.

  2. eLife assessment

    This valuable paper uses a cohort of SARS-CoV-2 infected people to link immune signatures 3 months post-infection with persistent, long COVID-19 symptoms. The strength of the evidence presented is solid based on a wide array of immunologic assays and a strategically designed cohort, with some claims that are incomplete based on a lack of specifically designed endpoints, lack of analysis of regulatory signals, and incomplete use of control samples. A couple of findings are novel and will be of interest to clinicians and immunologists, particularly that degree of inflammation at 3 months does not impair the generation of SARS-CoV-2 humoral and cellular memory responses and that cellular immune signatures are only somewhat correlated with long COVID-19 symptoms.

  3. Reviewer #1 (Public Review):

    In this study, authors examine immune signatures from patients that experienced mild, moderate, or severe COVID-19 symptoms and followed them for months to evaluate whether there was a correlation between their immune activation phenotypes, disease severity, and long COVID. Authors observed higher T cell activation/proliferation marker expression in blood samples of patients with severe disease whereas other cell types were more or less unchanged. The authors also examined the cytokine profile of the patient's serum samples to determine the potential drivers of T cell activation phenotypes. Authors then perform T-cell responses to viral peptides to determine the differences in activation phenotypes with disease severity.

    The major strengths of the paper appear in the evaluation of the appropriate cohort of human samples and following them over a period of months. Additionally, the authors perform detailed T-cell analysis in an unbiased way to determine any possible activation correlations with disease severity. The authors also perform antigen-specific T-cell analysis via peptide stimulation which adds to the overall findings. However, there are a number of drawbacks that need to be mentioned. Firstly, the phenotypes of T cells prior to the 3-month time-point are not known. Hence, there is no information on baseline or during the early phase of infection. Secondly, the response is largely obtained from blood. How much information about T cells in blood correlate with lung disease is a matter of concern. Analysis of lungs, where actual disease manifestation is ideal, however close to impossible in the human cohort. Alternatively, analysis of local lymph node aspirate or nasal swabs could be useful. Thirdly, the claim that bystander T cell activation plays a role seems loose, specifically the IL-15 in vitro data. Moreover, the analysis of T cells seems very focused on activation/proliferation phenotypes. Alternative T cell phenotypes such as regulatory, IL-10 producing, or FoxP3 expression are not extensively analyzed.

    Major points

    1. In Figure 1, the CD4 T cell activation phenotypes do not seem consistent across the groups. Why does moderate vs. severe show increases in CXCR3 expression but not mild vs. severe? The same goes for other markers. Performing T cell stimulation with class II peptides specific for CoV-2 and looking at IFN etc. to determine antigen-specific T cells and then gating on these activation/proliferation markers may be a better way to observe differences.

    2. One major drawback is the control patients. It would have helped to include a batch of samples from uninfected patients. Or to have the plasma/blood from patients before COVID-19 symptoms. This way there is a baseline for each group that could be compared. It is difficult to draw broad conclusions across the group at 3 months if we do not know their baseline phenotypes.

    3. Although the authors focused on activating/proliferating markers to correlate with disease severity, this analysis does not consider alternate T cell phenotypes such as the ones with regulatory or anti-inflammatory phenotypes. Did authors detect differences in T cells with regulatory profiles such as expression of IL-10, FoxP3, etc. in their unsupervised UMAP analysis or otherwise flow experiments?

  4. Reviewer #2 (Public Review):

    The manuscript is well written, the data are based on well-performed experiments, and the conclusions are supported by the data. The authors study thoroughly the global phenotype of T and NK cells and also analyze antigen-specific T cell frequencies. The data confirm that individuals who had severe COVID-19 disease (required ventilation and/or ITU admission) have slightly more activated CD4 and CD8 T cells at 3 months post-infection and report more frequently long COVID symptoms, yet the novelty of this manuscript is to show that these two are not linked to each other. Moreover, the manuscript confirms that patients across all disease severities mount and maintain memory T cell and antibody responses to SARS-CoV-2.

    In the introduction, the authors want to highlight the extent of patients who suffer from long COVID symptoms, yet it should be noted that these high frequencies (8-21%) are coming from unvaccinated and hospitalized patients (like those included in this study), while a large group of individuals experience asymptomatic SARS-CoV-2 infection, and these individuals are not integrated into these studies.

    The authors find that patients who recovered from severe COVID-19 3 months ago have more activated CD4+ and CD8+ T cells than patients who recovered from the mild disease. Although the difference is significant, the frequency of CD4+ T cells with an activated phenotype is increased only by about 2-fold (~2% vs ~1%), while the frequency of activated CD8+ T cells is about 6% vs 4%, which should be added to the results to better describe the extent of the activation.

    As the authors mention in the discussion, it cannot be excluded that the more activated T cell phenotype in patients who recovered from severe COVID-19 is not rather a consequence of the increased comorbidities associated with this group. However, their Luminex analysis of the serum shows that the levels of cytokines TNF-a, IL-4, IL-12, IL-15, and IL-17A decline by 8 and 12 months, suggesting that the immune activation by 3 months is most likely a consequence of the previous severe viral infection.
    To strengthen this point, PBMC is probably not available at a later time point, to see if the increased T cell activation decreases in line with the serum cytokines. Yet, the authors should at least try to repeat the experiments of coculturing CD3+ T cells from healthy volunteers with the serum of mild/severe patients at 8-12 months post-recovery (Fig. 3 D-E).

    The authors tried to find if the activated T cell phenotype or increased serum cytokines at 3 months post-infection is linked with increased long COVID symptoms. The study does not find any direct association when the data are adjusted for age, sex, and severity. This is the only novelty of this study, yet it is an important piece of information in the attempt to broaden our understanding of the underlying causes of long COVID symptoms.

    Overall, it would be important to understand if increased frequencies of T cell activation (~2-fold) and increased levels of serum cytokines at 3 months following severe COVID-19 that resulted in ventilation and/or ITU admission is specific to severe SARS-CoV-2 infection, or if similar consequences are resulting also from other severe acute viral infections. Addressing this question is beyond the scope of the manuscript, yet it should be discussed.

  5. Reviewer #3 (Public Review):

    In this paper, the authors used a cohort study to link immune signatures in blood 30 days after COVID-19 infection as possible predictors of prolonged symptomatology. The paper partially achieves its aims. While the selected analyses are comprehensive, the cohort design is appropriate and the mechanistic ex vivo work is clever and convincing, the strength of conclusions is somewhat limited by the selection of imprecise clinical endpoints, and the lack of analyses examining T regulatory signatures.

    Strengths of the paper are:
    • The paper includes a comprehensive and structured immune analysis.
    • The paper is extremely clearly written.
    • The use of manual gating and unsupervised analysis in Fig 1 is complementary and helpful.
    • Bystander T cell experiments with IL-15 are useful and attempt to explore mechanisms from human samples which are traditionally very challenging.
    • The experiments shown in Figure 4 documenting equal Cov2 T cell responses in all 3 cohorts are an extremely important result.

    Major concerns are:
    • The significance of the study is somewhat limited by the small sample size.
    • The symptomatic outcome scale for PASC is blunt and poorly captures severity. More state-of-the-start scales of symptomatic severity and heterogeneity exist for PASC. I suggest this and other papers as an example: https://pubmed.ncbi.nlm.nih.gov/36454631/
    • The omission of analyses examining T regulatory functions is a missed opportunity and these may be impaired in this population.
    • This is a challenging question that can be applied to many exploratory studies of this nature: how can we rule out the possibility that statistically significant differences in Figs 1, 2 & 3 are statistically significant but biologically meaningless? All cellular and cytokine measures of immune responses shown in these figures are not routinely measured in the clinic. Are there studies that can be cited to show that these differences are sufficient to have a causal impact on prolonged symptoms and tissue damage rather than just correlations with these outcomes?