Lower Viral Loads and Slower CD4+ T-Cell Count Decline in MRKAd5 HIV-1 Vaccinees Expressing Disease-Susceptible HLA-B*58:02
- Ellen M. Leitman ,
- Jacob Hurst ,
- Masahiko Mori ,
- James Kublin ,
- Thumbi Ndung'u ,
- Bruce D. Walker ,
- Jonathan M. Carlson ,
- Glenda E. Gray ,
- Philippa C. Matthews ,
- Nicole Frahm ,
- Philip J.R. Goulder
The Journal of infectious diseases | , Vol 214: pp. 379-389
Background. HLA strongly influences human immunodeficiency virus type 1 (HIV-1) disease progression. A major contributory mechanism is via the particular HLA-presented HIV-1 epitopes that are recognized by CD8+ T-cells. Different populations vary considerably in the HLA alleles expressed. We investigated the HLA-specific impact of the MRKAd5 HIV-1 Gag/Pol/Nef vaccine in a subset of the infected Phambili cohort in whom the disease-susceptible HLA-B*58:02 is highly prevalent.
Methods. Viral loads, CD4+ T-cell counts, and enzyme-linked immunospot assay–determined anti-HIV-1 CD8+ T-cell responses for a subset of infected antiretroviral-naive Phambili participants, selected according to sample availability, were analyzed.
Results. Among those expressing disease-susceptible HLA-B*58:02, vaccinees had a lower chronic viral set point than placebo recipients (median, 7240 vs 122 500 copies/mL; P = .01), a 0.76 log10 lower longitudinal viremia level (P = .01), and slower progression to a CD4+ T-cell count of <350 cells/mm3 (P = .02). These differences were accompanied by a higher Gag-specific breadth (4.5 vs 1 responses; P = .04) and magnitude (2300 vs 70 spot-forming cells/106peripheral blood mononuclear cells; P = .06) in vaccinees versus placebo recipients.
Conclusions. In addition to the known enhancement of HIV-1 acquisition resulting from the MRKAd5 HIV-1 vaccine, these findings in a nonrandomized subset of enrollees show an HLA-specific vaccine effect on the time to CD4+ T-cell count decline and viremia level after infection and the potential for vaccines to differentially alter disease outcome according to population HLA composition.
Clinical Trials Registration. NCT00413725, DOH-27-0207-1539.
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PhyloD
25 3 月, 2016
Machine learning tools for modeling viral adaptation to host immune responses.