The identification of biological predictors of adverse events following smallpox vaccination is of great public health interest. This is especially true today given efforts to defend the U.S. population against bioterrorism. Fortunately, we now have the ability to measure massive amounts of genetic, genomic, and proteomic information. Our ability to use this information to facilitate the identification of biomarkers of adverse events will largely depend on the architecture of the genotype-to-phenotype relationship. The process of innate and adaptive immunity is a complex trait that involves many biochemical and physiological pathways and thus many interacting genes. The complexity of the genotype-phenotype relationship suggests that we need a research strategy that embraces, rather than ignores, complexities due to gene-gene (GxG) and gene-environment (GxE) interactions. We propose here to develop, evaluate, implement, and distribute a comprehensive analytical strategy for identifying biomarkers of adverse events following smallpox vaccination. The proposed analytical strategy will combine novel and traditional statistical and computational methods for detecting GxG and GxE interactions with knowledge about hierarchical biological systems. This comprehensive analytical strategy will be used to identify biomarkers of adverse events among 103 volunteers that are part of an ongoing NIAID/NIH-sponsored trial to evaluate the Aventis Pasteur Smallpox Vaccine (APSV). Approximately half of these volunteers experienced adverse events. Genetic and proteomic immunological biomarker data are available for all 103 subjects at no cost to this study. We anticipate the analytical strategy and software developed as Part of this proposal will provide an important bioinformatics resource for all ongoing research Studies that have the goal of identifying combinations of biomarkers that predict adverse events Following vaccination for bioterrorism agents.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
1R01AI059694-01
Application #
6768402
Study Section
Special Emphasis Panel (ZRG1-SSS-H (90))
Program Officer
Challberg, Mark D
Project Start
2004-08-01
Project End
2009-05-31
Budget Start
2004-08-01
Budget End
2005-05-31
Support Year
1
Fiscal Year
2004
Total Cost
$486,051
Indirect Cost
Name
Dartmouth College
Department
Genetics
Type
Schools of Medicine
DUNS #
041027822
City
Hanover
State
NH
Country
United States
Zip Code
03755
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