期刊
PLOS ONE
卷 8, 期 5, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0064555
关键词
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资金
- National Institutes of Health (NIH) [U19 AI090019]
- NIH/NCRR CTSA award [UL1 RR025744]
- Ellison Foundation [AG-SS-1788]
- United States National Science Foundation Graduate Research Fellowship (NSF GRFP)
- Stanford Genome Training Program (SGTP
- NIH, United States National Human Genome Research Institute)
- Stanford Center on Longevity
- Donald E. and Delia B. Baxter Foundation Career Development Award
- National Heart, Lung, and Blood Institute (NHLBI) [HHSN288201000034C]
- Proteomics of Inflammatory Immunity and Pulmonary Arterial Hypertension
- NIH [5 U19-AI082719, 5 U19-AI050864, 5 U19-AI056363, 1 U19 AI090019, 4 U19 AI090019]
- Canadian Institutes of Health Research [2 OR-92141]
- Alliance for Lupus Research [21858]
- European Union Seventh Framework Programme [261382]
Background: Existing methods to measure influenza vaccine immunogenicity prohibit detailed analysis of epitope determinants recognized by immunoglobulins. The development of highly multiplex proteomics platforms capable of capturing a high level of antibody binding information will enable researchers and clinicians to generate rapid and meaningful readouts of influenza-specific antibody reactivity. Methods: We developed influenza hemagglutinin (HA) whole-protein and peptide microarrays and validated that the arrays allow detection of specific antibody reactivity across a broad dynamic range using commercially available antibodies targeted to linear and conformational HA epitopes. We derived serum from blood draws taken from 76 young and elderly subjects immediately before and 28 +/- 67 days post-vaccination with the 2008/2009 trivalent influenza vaccine and determined the antibody reactivity of these sera to influenza array antigens. Results: Using linear regression and correcting for multiple hypothesis testing by the Benjamini and Hochberg method of permutations over 1000 resamplings, we identified antibody reactivity to influenza whole-protein and peptide array features that correlated significantly with age, H1N1, and B-strain post-vaccine titer as assessed through a standard microneutralization assay (p<0.05, q<0.2). Notably, we identified several peptide epitopes that were inversely correlated with regard to age and seasonal H1N1 and B-strain neutralization titer (p<0.05, q<0.2), implicating reactivity to these epitopes in age-related defects in response to H1N1 influenza. We also employed multivariate linear regression with cross-validation to build models based on age and pre-vaccine peptide reactivity that predicted vaccine-induced neutralization of seasonal H1N1 and H3N2 influenza strains with a high level of accuracy (84.7% and 74.0%, respectively). Conclusion: Our methods provide powerful tools for rapid and accurate measurement of broad antibody-based immune responses to influenza, and may be useful in measuring response to other vaccines and infectious agents.
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