Are homeostatic mechanisms aiding the reconstitution of the T-cell pool during lymphopenia in humans?

A timely recovery of T-cell numbers following haematopoietic stem-cell transplantation (HSCT) is essential for preventing complications, such as increased risk of infection and disease relapse. In analogy to the occurrence of lymphopenia-induced proliferation in mice, T-cell dynamics in humans are thought to be homeostatically regulated in a cell density-dependent manner. The idea is that T cells divide faster and/or live longer when T-cell numbers are low, thereby helping the reconstitution of the T-cell pool. T-cell reconstitution after HSCT is, however, known to occur notoriously slowly. In fact, the evidence for the existence of homeostatic mechanisms in humans is quite ambiguous, since lymphopenia is often associated with infectious complications and immune activation, which confound the study of homeostatic regulation. This calls into question whether homeostatic mechanisms aid the reconstitution of the T-cell pool during lymphopenia in humans. Here we review the changes in T-cell dynamics in different situations of T-cell deficiency in humans, including the early development of the immune system after birth, healthy ageing, HIV infection, thymectomy and hematopoietic stem cell transplantation (HSCT). We discuss to what extent these changes in T-cell dynamics are a side-effect of increased immune activation during lymphopenia, and to what extent they truly reflect homeostatic mechanisms

Better safe than sorry: Naive T-cell dynamics in healthy ageing

It is well-known that the functioning of the immune system gradually deteriorates with age, and we are increasingly confronted with its consequences as the life expectancy of the human population increases. Changes in the T-cell pool are among the most prominent features of the changing immune system during healthy ageing, and changes in the naive T-cell pool in particular are generally held responsible for its gradual deterioration. These changes in the naive T-cell pool are thought to be due to involution of the thymus. It is commonly believed that the gradual loss of thymic output induces compensatory mechanisms to maintain the number of naive T cells at a relatively constant level, and induces a loss of diversity in the T-cell repertoire. Here we review the studies that support or challenge this widely-held view of immune ageing and discuss the implications for vaccination strategies

Effect of cellular aging on memory T-cell homeostasis

The fact that T-cell numbers remain relatively stable throughout life, and that T-cell proliferation rates increase during lymphopenia, has led to the consensus that T-cell numbers are regulated in a density-dependent manner. Competition for resources among memory T cells has been proposed to underlie this 'homeostatic' regulation. We first review how two classic models of resource competition affect the T-cell receptor (TCR) diversity of the memory T-cell pool. First, 'global' competition for cytokines leads to a skewed repertoire that tends to be dominated by the very first immune response. Second, additional 'cognate' competition for specific antigens results in a very diverse and stable memory T-cell pool, allowing every antigen to be remembered, which we therefore define as the 'gold-standard'. Because there is limited evidence that memory T cells of the same specificity compete more strongly with each other than with memory T cells of different specificities, i.e., for 'cognate' competition, we investigate whether cellular aging could account for a similar level of TCR diversity. We define cellular aging as a declining cellular fitness due to reduced proliferation. We find that the gradual erosion of previous T-cell memories due to cellular aging allows for better establishment of novel memories and for a much higher level of TCR diversity compared to global competition. A small continual source (either from stem-cell-like memory T-cells or from naive T-cells due to repeated antigen exposure) improves the diversity of the memory T-cell pool, but remarkably, only in the cellular aging model. We further show that the presence of a source keeps the inflation of chronic memory responses in check by maintaining the immune memories to non-chronic antigens. We conclude that cellular aging along with a small source provides a novel and immunologically realistic mechanism to achieve and maintain the 'gold-standard' level of TCR diversity in the memory T-cell pool

Disagreement FDA and EMA on RSV Maternal Vaccination: Possible Consequence for Global Mortality

The European Medicines Agency and the US Food and Drug Administration have recently approved a maternal vaccine for respiratory syncytial virus. The US Food and Drug Administration limits vaccination to later in pregnancy. Mathematical modeling demonstrates that this vaccination window may reduce the global mortality impact of the vaccine by 12%. Policymakers should carefully consider vaccine risks and benefits to safeguard vulnerable infants effectively

Explicit kinetic heterogeneity: mechanistic models for interpretation of labeling data of heterogeneous cell populations

Estimation of division and death rates of lymphocytes in different conditions is vital for quantitative understanding of the immune system. Deuterium, in the form of deuterated glucose or heavy water, can be used to measure rates of proliferation and death of lymphocytes in vivo. Inferring these rates from labeling and delabeling curves has been subject to considerable debate with different groups suggesting different mathematical models for that purpose. We show that the three models that are most commonly used are in fact mathematically identical and differ only in their interpretation of the estimated parameters. By extending these previous models, we here propose a more mechanistic approach for the analysis of data from deuterium labeling experiments. We construct a model of "kinetic heterogeneity" in which the total cell population consists of many sub-populations with different rates of cell turnover. In this model, for a given distribution of the rates of turnover, the predicted fraction of labeled DNA accumulated and lost can be calculated. Our model reproduces several previously made experimental observations, such as a negative correlation between the length of the labeling period and the rate at which labeled DNA is lost after label cessation. We demonstrate the reliability of the new explicit kinetic heterogeneity model by applying it to artificially generated datasets, and illustrate its usefulness by fitting experimental data. In contrast to previous models, the explicit kinetic heterogeneity model 1) provides a mechanistic way of interpreting labeling data; 2) allows for a non-exponential loss of labeled cells during delabeling, and 3) can be used to describe data with variable labeling length

Maternal vaccination against RSV can substantially reduce childhood mortality in low-income and middle-income countries: A mathematical modeling study

BACKGROUND: Respiratory syncytial virus (RSV) is a leading cause of childhood mortality in infants below 6 months of age. In low-income and middle-income countries (LMICs), the public health burden is substantial and resources are limited. It is critical to inform decision makers about effectiveness of new interventions. METHODS: We developed a mathematical model where individual RSV subtype A (RSV-A) and B (RSV-B) maternally derived neutralizing titers were predicted at time of birth after maternal vaccination with the RSV prefusion F protein-based vaccine. We estimated the subsequent duration of vaccine-induced immunity and compared this to the age at time of death distribution in the RSV GOLD Mortality Database to predict the potential impact of maternal vaccination on RSV-related childhood mortality. We used country-specific timing of antenatal care visits distributions and mortality estimates to make country-specific predictions for number of cases averted. FINDINGS: The model predicts that on average a neonate born at 40 weeks gestational age will be protected between 6 and 7 months from RSV-A and approximately 5 months from RSV-B related mortality. We estimated the potential impact of RSV-related mortality for in-hospital and out-of-hospital cases in LMICs and predicted that in 51 GAVI-eligible countries maternal vaccination could avert between 55% and 63% of the RSV-related in-hospital mortality cases below 6 months of age. INTERPRETATION: We show that maternal vaccination could substantially decrease RSV-A and RSV-B related in-hospital and out-of-hospital mortality in LMICs in the first 6 months of life

On the feasibility of using TCR sequencing to follow a vaccination response - lessons learned

T cells recognize pathogens by their highly specific T-cell receptor (TCR), which can bind small fragments of an antigen presented on the Major Histocompatibility Complex (MHC). Antigens that are provided through vaccination cause specific T cells to respond by expanding and forming specific memory to combat a future infection. Quantification of this T-cell response could improve vaccine monitoring or identify individuals with a reduced ability to respond to a vaccination. In this proof-of-concept study we use longitudinal sequencing of the TCRβ repertoire to quantify the response in the CD4+ memory T-cell pool upon pneumococcal conjugate vaccination. This comes with several challenges owing to the enormous size and diversity of the T-cell pool, the limited frequency of vaccine-specific TCRs in the total repertoire, and the variation in sample size and quality. We defined quantitative requirements to classify T-cell expansions and identified critical parameters that aid in reliable analysis of the data. In the context of pneumococcal conjugate vaccination, we were able to detect robust T-cell expansions in a minority of the donors, which suggests that the T-cell response against the conjugate in the pneumococcal vaccine is small and/or very broad. These results indicate that there is still a long way to go before TCR sequencing can be reliably used as a personal biomarker for vaccine-induced protection. Nevertheless, this study highlights the importance of having multiple samples containing sufficient T-cell numbers, which will support future studies that characterize T-cell responses using longitudinal TCR sequencing

On the feasibility of using TCR sequencing to follow a vaccination response – lessons learned

T cells recognize pathogens by their highly specific T-cell receptor (TCR), which can bind small fragments of an antigen presented on the Major Histocompatibility Complex (MHC). Antigens that are provided through vaccination cause specific T cells to respond by expanding and forming specific memory to combat a future infection. Quantification of this T-cell response could improve vaccine monitoring or identify individuals with a reduced ability to respond to a vaccination. In this proof-of-concept study we use longitudinal sequencing of the TCRβ repertoire to quantify the response in the CD4+ memory T-cell pool upon pneumococcal conjugate vaccination. This comes with several challenges owing to the enormous size and diversity of the T-cell pool, the limited frequency of vaccine-specific TCRs in the total repertoire, and the variation in sample size and quality. We defined quantitative requirements to classify T-cell expansions and identified critical parameters that aid in reliable analysis of the data. In the context of pneumococcal conjugate vaccination, we were able to detect robust T-cell expansions in a minority of the donors, which suggests that the T-cell response against the conjugate in the pneumococcal vaccine is small and/or very broad. These results indicate that there is still a long way to go before TCR sequencing can be reliably used as a personal biomarker for vaccine-induced protection. Nevertheless, this study highlights the importance of having multiple samples containing sufficient T-cell numbers, which will support future studies that characterize T-cell responses using longitudinal TCR sequencing

Multi-omics approach identifies PI3 as a biomarker for disease severity and hyper-keratinization in psoriasis

BACKGROUND: Psoriasis is an immune-mediated inflammatory skin disease. Psoriasis severity evaluation is important for clinicians in the assessment of disease severity and subsequent clinical decision making. However, no objective biomarker is available for accurately evaluating disease severity in psoriasis. OBJECTIVE: To define and compare biomarkers of disease severity and progression in psoriatic skin. METHODS: We performed proteome profiling to study the proteins circulating in the serum from patients with psoriasis, psoriatic arthritis and ankylosing spondylitis, and transcriptome sequencing to investigate the gene expression in skin from the same cohort. We then used machine learning approaches to evaluate different biomarker candidates across several independent cohorts. In order to reveal the cell-type specificity of different biomarkers, we also analyzed a single-cell dataset of skin samples. In-situ staining was applied for the validation of biomarker expression. RESULTS: We identified that the peptidase inhibitor 3 (PI3) was significantly correlated with the corresponding local skin gene expression, and was associated with disease severity. We applied machine learning methods to confirm that PI3 was an effective psoriasis classifier, Finally, we validated PI3 as psoriasis biomarker using in-situ staining and public datasets. Single-cell data and in-situ staining indicated that PI3 was specifically highly expressed in keratinocytes from psoriatic lesions. CONCLUSION: Our results suggest that PI3 may be a psoriasis-specific biomarker for disease severity and hyper-keratinization

Abundance of Early Functional HIV-Specific CD8+ T Cells Does Not Predict AIDS-Free Survival Time

Background T-cell immunity is thought to play an important role in controlling HIV infection, and is a main target for HIV vaccine development. HIV-specific central memory CD8+ and CD4+ T cells producing IFNγ and IL-2 have been associated with control of viremia and are therefore hypothesized to be truly protective and determine subsequent clinical outcome. However, the cause-effect relationship between HIV-specific cellular immunity and disease progression is unknown. We investigated in a large prospective cohort study involving 96 individuals of the Amsterdam Cohort Studies with a known date of seroconversion whether the presence of cytokine-producing HIV-specific CD8+ T cells early in infection was associated with AIDS-free survival time. Methods and Findings The number and percentage of IFNγ and IL-2 producing CD8+ T cells was measured after in vitro stimulation with an overlapping Gag-peptide pool in T cells sampled approximately one year after seroconversion. Kaplan-Meier survival analysis and Cox proportional hazard models showed that frequencies of cytokine-producing Gag-specific CD8+ T cells (IFNγ, IL-2 or both) shortly after seroconversion were neither associated with time to AIDS nor with the rate of CD4+ T-cell decline. Conclusions These data show that high numbers of functional HIV-specific CD8+ T cells can be found early in HIV infection, irrespective of subsequent clinical outcome. The fact that both progressors and long-term non-progressors have abundant T cell immunity of the specificity associated with low viral load shortly after seroconversion suggests that the more rapid loss of T cell immunity observed in progressors may be a consequence rather than a cause of disease progression