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Cell. 2014 Apr 10;157(2):499-513. doi: 10.1016/j.cell.2014.03.031.

Global analyses of human immune variation reveal baseline predictors of postvaccination responses.

Author information

1
Trans-NIH Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA; Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: john.tsang@nih.gov.
2
Trans-NIH Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA; Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA. Electronic address: pams@nhgri.nih.gov.
3
Trans-NIH Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA.
4
Trans-NIH Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA; Lymphocyte Biology Section, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
5
Trans-NIH Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA; Department of Transfusion Medicine, Clinical Center, National Institutes of Health, Bethesda, MD 20892, USA.
6
Trans-NIH Center for Human Immunology, Autoimmunity and Inflammation, National Institutes of Health, Bethesda, MD 20892, USA; Hematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
7
Systems Genomics and Bioinformatics Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
8
Laboratory of Retrovirus Research, US Food and Drug Administration, Bethesda, MD 20892, USA.
9
Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.

Erratum in

  • Cell. 2014 Jul 3;158(1):226.

Abstract

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.

PMID:
24725414
PMCID:
PMC4139290
DOI:
10.1016/j.cell.2014.03.031
[Indexed for MEDLINE]
Free PMC Article

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