Autor: |
Mark M. Davis, Damien Chaussabel, David A. Hafler, Susan M. Kaech, Jacob Frelinger, Yuri Kotliarov, Damian Fermin, Evan Henrich, Raphael Gottardo, A. Karolina Palucka, Albert C. Shaw, Purvesh Khatri, Ruth R. Montgomery, Kenneth Stuart, Jean H. Wilson, John S. Tsang, Robert B. Belshe, Heidi J Zapata, Nicole Baldwin, Subhasis Mohanty, Renaud Gaujoux, Samit R Joshi, Ellis L. Reinherz, Barbara Siconolfi, G.A. Poland, Renan Sauteraud, Jeanine Baisch, Diane E. Grill, Bali Pulendran, Hailong Meng, Richard B. Kennedy, Gerlinde Obermoser, Virginia Pascual, Ikuyo Ueda, Esperanza Anguiano, Tamara P. Blevins, Ann L. Oberg, Erol Fikrig, Steven H. Kleinstein, Foo Cheung, Stefan Avey, Sui Tsang, Francesco Vallania, Inna G. Ovsyannikova, Shai S. Shen-Orr |
Rok vydání: |
2017 |
Předmět: |
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Zdroj: |
Science Immunology. 2 |
ISSN: |
2470-9468 |
Popis: |
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. |
Databáze: |
OpenAIRE |
Externí odkaz: |
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