Broad and Gag-Biased HIV-1 Epitope Repertoires are Associated with Lower Viral Loads
Rousseau, Christine M.
Mullins, James I.
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CitationRolland, Morgane, David Heckerman, Wenjie Deng, Christine M. Rousseau, Hoosen Coovadia, Karen Bishop, Philip J. R. Goulder, Bruce D. Walker, Christian Brander, and James I. Mullins. 2008. Broad and gag-biased HIV-1 epitope repertoires are associated with lower viral loads. PLoS ONE 3(1): e1424.
AbstractBackground: HLA class-I alleles differ in their ability to control HIV replication through cell-mediated immune responses. No consistent associations have been found between the breadth of Cytotoxic T Lymphocytes (CTL) responses and the control of HIV-1, and it is unknown whether the size or distribution of the viral proteome-wide epitope repertoire, i.e., the intrinsic ability to present fewer, more or specific viral epitopes, could affect clinical markers of disease progression. Methodology/Principal Findings: We used an epitope prediction model to identify all epitope motifs in a set of 302 HIV-1 full-length proteomes according to each individual's HLA (Human Leukocyte Antigen) genotype. The epitope repertoire, i.e., the number of predicted epitopes per HIV-1 proteome, varied considerably between HLA alleles and thus among individual proteomes. In a subgroup of 270 chronically infected individuals, we found that lower viral loads and higher CD4 counts were associated with a larger predicted epitope repertoire. Additionally, in Gag and Rev only, more epitopes were restricted by alleles associated with low viral loads than by alleles associated with higher viral loads. Conclusions/Significance: This comprehensive analysis puts forth the epitope repertoire as a mechanistic component of the multi-faceted HIV-specific CTL response. The favorable impact on markers of disease status of the propensity to present more HLA binding peptides and specific proteins gives impetus to vaccine design strategies that seek to elicit responses to a broad array of HIV-1 epitopes, and suggest a particular focus on Gag.
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