In this Project 2 entitled """"""""T cell and General Immune Responses to Influenza,"""""""" we focus on general immunological biomarkers and antigen specific T cells in a continuing effort to define the immune response to influenza vaccination in volunteers from different age groups and especially utilizing the twin cohorts of SRI. We hope to establish benchmarks of immune proficiency in these different cohorts that will be predictive not just of an influenza response, but of immunological """"""""health,"""""""" or at least a component of it, in general.
In Aim 1, we will continue our ongoing program to survey the blood samples of volunteers being immunized for a broad array of serum cytokines, white blood cell subsets, lymphocyte proliferation, and whole genome gene expression. Using the twin cohorts, we will be able to ask what traits are determined genetically, and of those evident in young adults, which change in older adults. Also a high priority is what traits correlate with a robust or poor response.
in Aim 2 and 3, we will take advantage of recent advances in peptide-MHC tetramer technology together with our own efforts to probe more broadly and deeply into the nature of the T cell response to different influenza antigens. Thus, we will survey dozens of different T cell epitopes at once to ask whether or not there are specific changes in influenza specific T cell repertoires with age and to what extent does genetics contribute to the repertoire. We will also ask how the different influenza vaccine types influence the repertoire of responding T cells and whether or not there is a correlation between the repertoire used, and a robust or poor response. We have also been able recently to isolate antigen specific naive populations of T cells (which are in the cytokines produced in the signaling pathways utilized;in some cases, only 1 in one million cells of the CD8+ T cell pool). This gives us the ability to probe the naive repertoire of strain-specific T cells in young adults and characterize their response to different types of influenza vaccination. Lastly, in Aim 4, we propose to use """"""""humanized"""""""" mice to test hypotheses generated in the first three aims.

Public Health Relevance

We seek to understand at multiple levels-molecular, cellular and organismal?how the immune systems of humans in different age groups are constituted and how their T lymphocytes respond or fail to defend against specific influenza strains. It is expected that the assays that will result from these studies will aid in the development of more effective vaccines and an understanding of immunological

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI057229-09
Application #
8375626
Study Section
Special Emphasis Panel (ZAI1-KS-I)
Project Start
Project End
Budget Start
2012-04-01
Budget End
2013-03-31
Support Year
9
Fiscal Year
2012
Total Cost
$210,932
Indirect Cost
$68,741
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Keeffe, Jennifer R; Van Rompay, Koen K A; Olsen, Priscilla C et al. (2018) A Combination of Two Human Monoclonal Antibodies Prevents Zika Virus Escape Mutations in Non-human Primates. Cell Rep 25:1385-1394.e7
Wagar, Lisa E; DiFazio, Robert M; Davis, Mark M (2018) Advanced model systems and tools for basic and translational human immunology. Genome Med 10:73
Good, Zinaida; Sarno, Jolanda; Jager, Astraea et al. (2018) Single-cell developmental classification of B cell precursor acute lymphoblastic leukemia at diagnosis reveals predictors of relapse. Nat Med 24:474-483
Satpathy, Ansuman T; Saligrama, Naresha; Buenrostro, Jason D et al. (2018) Transcript-indexed ATAC-seq for precision immune profiling. Nat Med 24:580-590
Vallania, Francesco; Tam, Andrew; Lofgren, Shane et al. (2018) Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases. Nat Commun 9:4735
Bongen, Erika; Vallania, Francesco; Utz, Paul J et al. (2018) KLRD1-expressing natural killer cells predict influenza susceptibility. Genome Med 10:45
Sweeney, Timothy E; Azad, Tej D; Donato, Michele et al. (2018) Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters. Crit Care Med 46:915-925
Lin, Dongxia; Maecker, Holden T (2018) Mass Cytometry Assays for Antigen-Specific T Cells Using CyTOF. Methods Mol Biol 1678:37-47
Goltsev, Yury; Samusik, Nikolay; Kennedy-Darling, Julia et al. (2018) Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging. Cell 174:968-981.e15
Gee, Marvin H; Sibener, Leah V; Birnbaum, Michael E et al. (2018) Stress-testing the relationship between T cell receptor/peptide-MHC affinity and cross-reactivity using peptide velcro. Proc Natl Acad Sci U S A 115:E7369-E7378

Showing the most recent 10 out of 249 publications