Dataset Information

Human circulating influenza-CD4+ ICOS1+IL-21+ T cells expand after vaccination, exert helper function, and predict antibody responses.

ABSTRACT: Protection against influenza is mediated by neutralizing antibodies, and their induction at high and sustained titers is key for successful vaccination. Optimal B cells activation requires delivery of help from CD4(+) T lymphocytes. In lymph nodes and tonsils, T-follicular helper cells have been identified as the T cells subset specialized in helping B lymphocytes, with interleukin-21 (IL-21) and inducible costimulatory molecule (ICOS1) playing a central role for this function. We followed the expansion of antigen-specific IL-21(+) CD4(+) T cells upon influenza vaccination in adults. We show that, after an overnight in vitro stimulation, influenza-specific IL-21(+) CD4(+) T cells can be measured in human blood, accumulate in the CXCR5(-)ICOS1(+) population, and increase in frequency after vaccination. The expansion of influenza-specific ICOS1(+)IL-21(+) CD4(+) T cells associates with and predicts the rise of functionally active antibodies to avian H5N1. We also show that blood-derived CXCR5(-)ICOS1(+) CD4(+) T cells exert helper function in vitro and support the differentiation of influenza specific B cells in an ICOS1- and IL-21-dependent manner. We propose that the expansion of antigen-specific ICOS1(+)IL-21(+) CD4(+) T cells in blood is an early marker of vaccine immunogenicity and an important immune parameter for the evaluation of novel vaccination strategies.

SUBMITTER: Spensieri F

PROVIDER: S-EPMC3761599 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Human circulating influenza-CD4+ ICOS1+IL-21+ T cells expand after vaccination, exert helper function, and predict antibody responses.

Spensieri Fabiana F Borgogni Erica E Zedda Luisanna L Bardelli Monia M Buricchi Francesca F Volpini Gianfranco G Fragapane Elena E Tavarini Simona S Finco Oretta O Rappuoli Rino R Del Giudice Giuseppe G Galli Grazia G Castellino Flora F

Proceedings of the National Academy of Sciences of the United States of America 20130812 35

Protection against influenza is mediated by neutralizing antibodies, and their induction at high and sustained titers is key for successful vaccination. Optimal B cells activation requires delivery of help from CD4(+) T lymphocytes. In lymph nodes and tonsils, T-follicular helper cells have been identified as the T cells subset specialized in helping B lymphocytes, with interleukin-21 (IL-21) and inducible costimulatory molecule (ICOS1) playing a central role for this function. We followed the e ...[more]

PMID: 23940329

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Project description:ObjectiveCirculating follicular helper T (cTfh) cells are a specialized subset of CD4+ T cells that express the CXC-chemokine receptor 5 (CXCR5). These cells exhibit immune activities by inducing B cell differentiation and proliferation via the secretion of interleukin (IL)-21. Multiple studies have demonstrated that cTfh cells are associated with the progression and severity of numerous diseases. To investigate the role of cTfh cells in the development of Kawasaki disease (KD), we analyzed the distinct subpopulations of cTfh cells and serum IL-21 levels in different phases of KD.MethodsAccording to the differential expression of inducible co-stimulator (ICOS) and programmed cell death protein 1 (PD-1), cTfh cells were divided into distinct subsets. We used flow cytometry and flow cytometric bead arrays (CBA) to analyze subsets of CD4+CXCR5+ T cells and serum IL-21 levels. The samples were collected from control subjects and Kawasaki disease patients in the acute and remission phases.ResultsIn the acute phase (AP), the percentages of ICOShighPD-1high, ICOS+PD-1+, ICOS-PD-1+, CD45RA-IL-21+ cTfh cells and serum IL-21 levels significantly increased. Furthermore, the percentages of ICOShighPD-1high and ICOS+PD-1+ cTfh cells positively correlated with erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) values, whereas the percentage of ICOS-PD-1+ cTfh cells indicated negative correlations. The percentages of ICOS+PD-1+, ICOShighPD-1high and CD45RA-IL-21+ cTfh cells correlated positively with serum IL-21 levels. In the remission phase (RP), the percentages of ICOS-PD-1+, CD45RA-IL-21+ cTfh cells and serum IL-21 levels were significantly decreased. In contrast, the percentages of ICOS+PD-1+, ICOShighPD-1high, and ICOS+PD-1- cTfh cells were further increased. Among these subsets, only CD45RA-IL-21+ cTfh cells correlated positively with serum IL-21 levels.ConclusionsThe present study is the first investigation that examined the distribution of circulating cTfh cell subsets in Kawasaki disease. Both cTfh cells and serum IL-21 are essential to the pathogenesis of KD. Our study provides further understanding of the immune response involved in KD and offers novel insights in the pathogenetic mechanism of this disease.

Project description:MotivationSystems immunology leverages recent technological advancements that enable broad profiling of the immune system to better understand the response to infection and vaccination, as well as the dysregulation that occurs in disease. An increasingly common approach to gain insights from these large-scale profiling experiments involves the application of statistical learning methods to predict disease states or the immune response to perturbations. However, the goal of many systems studies is not to maximize accuracy, but rather to gain biological insights. The predictors identified using current approaches can be biologically uninterpretable or present only one of many equally predictive models, leading to a narrow understanding of the underlying biology.ResultsHere we show that incorporating prior biological knowledge within a logistic modeling framework by using network-level constraints on transcriptional profiling data significantly improves interpretability. Moreover, incorporating different types of biological knowledge produces models that highlight distinct aspects of the underlying biology, while maintaining predictive accuracy. We propose a new framework, Logistic Multiple Network-constrained Regression (LogMiNeR), and apply it to understand the mechanisms underlying differential responses to influenza vaccination. Although standard logistic regression approaches were predictive, they were minimally interpretable. Incorporating prior knowledge using LogMiNeR led to models that were equally predictive yet highly interpretable. In this context, B cell-specific genes and mTOR signaling were associated with an effective vaccination response in young adults. Overall, our results demonstrate a new paradigm for analyzing high-dimensional immune profiling data in which multiple networks encoding prior knowledge are incorporated to improve model interpretability.Availability and implementationThe R source code described in this article is publicly available at https://bitbucket.org/kleinstein/logminer .Contactsteven.kleinstein@yale.edu or stefan.avey@yale.edu.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Human circulating influenza-CD4+ ICOS1+IL-21+ T cells expand after vaccination, exert helper function, and predict antibody responses.

Publications

Human circulating influenza-CD4+ ICOS1+IL-21+ T cells expand after vaccination, exert helper function, and predict antibody responses.

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