DNA variations impact immune host response through the perturbations they cause to transcriptional and biological networks, providing a molecular phenotype* that is an intermediate to the clinical phenotype. By integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data, we are now able to infer transcriptional networks capable of representing causal relationships among genes and traits in the network. This provides the opportunity to identify multiple genetic perturbations that alter the states of molecular networks and that in turn move systems into disease states. Specifically, by dissecting immunogenetic traits, we are able to elucidate key drivers of immune host response beyond what could be achieved by traditional genetic association studies alone. The Systems Immunogenetics core (Core D) will provide critical statistical genetics and computational biology expertise to the U19 investigators across all projects by guiding experimental design with appropriate biostatistical oversight, providing state-of-the-art systems genetics analysis and modeling approaches and ensuring that the vast amounts of data generated are rapidly integrated to identify key genetic regulators of immune phenotype and response to SARS, Influenza and West Nile Viruses.

Public Health Relevance

The Systems Immunogenetics Core provides the blostatistical and computational modeling expertise to elucidate the genetic basis of host immune response and to use this knowledge to aid in prioritization and identification of targets for therapeutic intervention.

Agency
National Institute of Health (NIH)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI100625-03
Application #
8706031
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
Budget End
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
University of North Carolina Chapel Hill
Department
Type
DUNS #
City
Chapel Hill
State
NC
Country
United States
Zip Code
Ferris, Martin T; Heise, Mark T (2014) Quantitative genetics in the study of virus-induced disease. Adv Virus Res 88:193-225
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