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High-dimensional immunomonitoring models of HIV-1–specific CD8 T-cell responses accurately identify subjects achieving spontaneous viral control

Zaza M. Ndhlovu, Lori B. Chibnik, Jacqueline Proudfoot, Seanna Vine, Ashley McMullen, Kevin Cesa, Filippos Porichis, R. Brad Jones, Donna Marie Alvino, Meghan G. Hart, Eleni Stampouloglou, Alicja Piechocka-Trocha, Carl Kadie, Florencia Pereyra, David Heckerman, Philip L. De Jager, Bruce D. Walker, Daniel E. Kaufmann

Key Points

  • Immune monitoring models integrating multiple functions of HIV-1–specific CD8 T cells distinguish controllers from subjects with progressive HIV-1 infection.

  • This strategy may have important applications in predictive model development and immune monitoring of HIV-1 vaccine trials.

Abstract

The development of immunomonitoring models to determine HIV-1 vaccine efficacy is a major challenge. Studies suggest that HIV-1–specific CD8 T cells play a critical role in subjects achieving spontaneous viral control (HIV-1 controllers) and that they will be important in immune interventions. However, no single CD8 T-cell function is uniquely associated with controller status and the heterogeneity of responses targeting different epitopes further complicates the discovery of determinants of protective immunity. In the present study, we describe immunomonitoring models integrating multiple functions of epitope-specific CD8 T cells that distinguish controllers from subjects with treated or untreated progressive infection. Models integrating higher numbers of variables and trained with the least absolute shrinkage and selection operator (LASSO) variant of logistic regression and 10-fold cross-validation produce “diagnostic tests” that display an excellent capacity to delineate subject categories. The test accuracy reaches 75% area under the receiving operating characteristic curve in cohorts matched for prevalence of protective alleles. Linear mixed-effects model analyses show that the proliferative capacity, cytokine production, and kinetics of cytokine secretion are associated with HIV-1 control. Although proliferative capacity is the strongest single discriminant, integrated modeling of different dimensions of data leverages individual associations. This strategy may have important applications in predictive model development and immune monitoring of HIV-1 vaccine trials.

  • Submitted June 11, 2012.
  • Accepted November 9, 2012.
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