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  • Clonal Deletion Prunes but Does Not Eliminate Self-Specific alpha beta CD8(+) T Lymphocytes IMMUNITY Yu, W., Jiang, N., Ebert, P. J., Kidd, B. A., Mueller, S., Lund, P. J., Juang, J., Adachi, K., Tse, T., Birnbaum, M. E., Newell, E. W., Wilson, D. M., Grotenbreg, G. M., Valitutti, S., Quake, S. R., Davis, M. M. 2015; 42 (5): 929-941


    It has long been thought that clonal deletion efficiently removes almost all self-specific T cells from the peripheral repertoire. We found that self-peptide MHC-specific CD8(+) T cells in the blood of healthy humans were present in frequencies similar to those specific for non-self antigens. For the Y chromosome-encoded SMCY antigen, self-specific T cells exhibited only a 3-fold lower average frequency in males versus females and were anergic with respect to peptide activation, although this inhibition could be overcome by a stronger stimulus. We conclude that clonal deletion prunes but does not eliminate self-specific T cells and suggest that to do so would create holes in the repertoire that pathogens could readily exploit. In support of this hypothesis, we detected T cells specific for all 20 amino acid variants at the p5 position of a hepatitis C virus epitope in a random group of blood donors.

    View details for DOI 10.1016/j.immuni.2015.05.001

    View details for Web of Science ID 000354827400018

  • Apoptosis and other immune biomarkers predict influenza vaccine responsiveness. Molecular systems biology Furman, D., Jojic, V., Kidd, B., Shen-Orr, S., Price, J., Jarrell, J., Tse, T., Huang, H., Lund, P., Maecker, H. T., Utz, P. J., Dekker, C. L., Koller, D., Davis, M. M. 2013; 9: 659-?


    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.

    View details for DOI 10.1038/msb.2013.15

    View details for PubMedID 23591775

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