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      Stereotypic Immune System Development in Newborn Children

      Cell
      Elsevier BV

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          Systems biology approach predicts immunogenicity of the yellow fever vaccine in humans.

          A major challenge in vaccinology is to prospectively determine vaccine efficacy. Here we have used a systems biology approach to identify early gene 'signatures' that predicted immune responses in humans vaccinated with yellow fever vaccine YF-17D. Vaccination induced genes that regulate virus innate sensing and type I interferon production. Computational analyses identified a gene signature, including complement protein C1qB and eukaryotic translation initiation factor 2 alpha kinase 4-an orchestrator of the integrated stress response-that correlated with and predicted YF-17D CD8(+) T cell responses with up to 90% accuracy in an independent, blinded trial. A distinct signature, including B cell growth factor TNFRS17, predicted the neutralizing antibody response with up to 100% accuracy. These data highlight the utility of systems biology approaches in predicting vaccine efficacy.
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            Maternal alloantigens promote the development of tolerogenic fetal regulatory T cells in utero.

            As the immune system develops, T cells are selected or regulated to become tolerant of self antigens and reactive against foreign antigens. In mice, the induction of such tolerance is thought to be attributable to the deletion of self-reactive cells. Here, we show that the human fetal immune system takes advantage of an additional mechanism: the generation of regulatory T cells (Tregs) that suppress fetal immune responses. We find that substantial numbers of maternal cells cross the placenta to reside in fetal lymph nodes, inducing the development of CD4+CD25highFoxP3+ Tregs that suppress fetal antimaternal immunity and persist at least until early adulthood. These findings reveal a form of antigen-specific tolerance in humans, induced in utero and probably active in regulating immune responses after birth.
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              Global analyses of human immune variation reveal baseline predictors of postvaccination responses.

              A major goal of systems biology is the development of models that accurately predict responses to perturbation. Constructing such models requires the collection of dense measurements of system states, yet transformation of data into predictive constructs remains a challenge. To begin to model human immunity, we analyzed immune parameters in depth both at baseline and in response to influenza vaccination. Peripheral blood mononuclear cell transcriptomes, serum titers, cell subpopulation frequencies, and B cell responses were assessed in 63 individuals before and after vaccination and were used to develop a systematic framework to dissect inter- and intra-individual variation and build predictive models of postvaccination antibody responses. Strikingly, independent of age and pre-existing antibody titers, accurate models could be constructed using pre-perturbation cell populations alone, which were validated using independent baseline time points. Most of the parameters contributing to prediction delineated temporally stable baseline differences across individuals, raising the prospect of immune monitoring before intervention.
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                Author and article information

                Journal
                10.1016/j.cell.2018.06.045
                http://creativecommons.org/licenses/by-nc-nd/4.0/

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