4.7 Article

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

Journal

NATURE IMMUNOLOGY
Volume 10, Issue 1, Pages 116-125

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/ni.1688

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Funding

  1. US National Institutes of Health
  2. Sanofi Pasteur
  3. Bill & Melinda Gates Foundation
  4. [U19 AI057266]
  5. [R01 AI048638]
  6. [R01 DK057665]
  7. [U54 AI057157]
  8. [N01 AI50019]
  9. [N01 AI50025]
  10. NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES [UL1TR000454] Funding Source: NIH RePORTER
  11. NATIONAL CENTER FOR RESEARCH RESOURCES [UL1RR025008] Funding Source: NIH RePORTER
  12. NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [N01AI050025, U54AI057157, U19AI057266, R01AI048638, U19AI090023] Funding Source: NIH RePORTER
  13. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [R01DK057665, R37DK057665] Funding Source: NIH RePORTER

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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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