Abstract
Despite the importance of the immune system in many diseases, there are currently no objective benchmarks of immunological health. In an effort to identifying such markers, we used influenza vaccination in 30 young (20-30 years) and 59 older subjects (60 to >89 years) as models for strong and weak immune responses, respectively, and assayed their serological responses to influenza strains as well as a wide variety of other parameters, including gene expression, antibodies to hemagglutinin peptides, serum cytokines, cell subset phenotypes and in vitro cytokine stimulation. Using machine learning, we identified nine variables that predict the antibody response with 84% accuracy. Two of these variables are involved in apoptosis, which positively associated with the response to vaccination and was confirmed to be a contributor to vaccine responsiveness in mice. The identification of these biomarkers provides new insights into what immune features may be most important for immune health.
| Original language | English |
|---|---|
| Article number | 659 |
| Journal | Molecular Systems Biology |
| Volume | 9 |
| DOIs | |
| State | Published - 2013 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- aging
- apoptosis
- influenza
- systems immunology
- vaccinology
All Science Journal Classification (ASJC) codes
- Information Systems
- General Biochemistry,Genetics and Molecular Biology
- General Immunology and Microbiology
- General Agricultural and Biological Sciences
- Computational Theory and Mathematics
- Applied Mathematics
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