Multicohort analysis reveals baseline transcriptional predictors of influenza vaccination responses

Stefan Avey, Foo Cheung, Damian Fermin, Jacob Frelinger, Renaud Gaujoux, Raphael Gottardo, Purvesh Khatri, Steven H. Kleinstein, Yuri Kotliarov, Hailong Meng, Renan Sauteraud, Shai S. Shen-Orr, John S. Tsang, Francesco Vallania, Esperanza Anguiano, Jeanine Baisch, Nicole Baldwin, Robert B. Belshe, Tamara P. Blevins, Damien ChaussabelMark M. Davis, Erol Fikrig, Diane E. Grill, David A. Hafler, Evan Henrich, Samit R. Joshi, Susan M. Kaech, Rick B. Kennedy, Subhasis Mohanty, Ruth R. Montgomery, Ann L. Oberg, Gerlinde Obermoser, Inna G. Ovsyannikova, A. Karolina Palucka, Virginia Pascual, Greg A. Poland, Bali Pulendran, Ellis L. Reinherz, Albert C. Shaw, Barbara Siconolfi, Kenneth D. Stuart, Sui Tsang, Ikuyo Ueda, Jean Wilson, Heidi J. Zapata

Research output: Contribution to journalArticle

13 Scopus citations

Abstract

Annual influenza vaccinations are currently recommended for all individuals 6 months and older. Antibodies induced by vaccination are an important mechanism of protection against infection. Despite the overall public health success of influenza vaccination, many individuals fail to induce a substantial antibody response. Systems-level immune profiling studies have discerned associations between transcriptional and cell subset signatures with the success of antibody responses. However, existing signatures have relied on small cohorts and have not been validated in large independent studies. We leveraged multiple influenza vaccination cohorts spanning distinct geographical locations and seasons from the Human Immunology Project Consortium (HIPC) and the Center for Human Immunology (CHI) to identify baseline (i.e., before vaccination) predictive transcriptional signatures of influenza vaccination responses. Our multicohort analysis of HIPC data identified nine genes (RAB24, GRB2, DPP3, ACTB, MVP, DPP7, ARPC4, PLEKHB2, and ARRB1) and three gene modules that were significantly associated with the magnitude of the antibody response, and these associations were validated in the independent CHI cohort. These signatures were specific to young individuals, suggesting that distinct mechanisms underlie the lower vaccine response in older individuals. We found an inverse correlation between the effect size of signatures in young and older individuals. Although the presence of an inflammatory gene signature, for example, was associated with better antibody responses in young individuals, it was associated with worse responses in older individuals. These results point to the prospect of predicting antibody responses before vaccination and provide insights into the biological mechanisms underlying successful vaccination responses.

Original languageEnglish (US)
Article numbereaal4656
JournalScience Immunology
Volume2
Issue number14
DOIs
StatePublished - Apr 25 2017

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology

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    Avey, S., Cheung, F., Fermin, D., Frelinger, J., Gaujoux, R., Gottardo, R., Khatri, P., Kleinstein, S. H., Kotliarov, Y., Meng, H., Sauteraud, R., Shen-Orr, S. S., Tsang, J. S., Vallania, F., Anguiano, E., Baisch, J., Baldwin, N., Belshe, R. B., Blevins, T. P., ... Zapata, H. J. (2017). Multicohort analysis reveals baseline transcriptional predictors of influenza vaccination responses. Science Immunology, 2(14), [eaal4656]. https://doi.org/10.1126/sciimmunol.aal4656