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. 2024 Jan;103(1):e15298.
doi: 10.1111/tan.15298. Epub 2023 Nov 14.

Impact of predicted HLA class I immunopeptidome on viral reservoir in a cohort of people living with HIV in Italy

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Impact of predicted HLA class I immunopeptidome on viral reservoir in a cohort of people living with HIV in Italy

Pier Edoardo Rovatti et al. HLA. 2024 Jan.

Abstract

The class I HLA genotype has been widely recognized as a factor influencing HIV disease progression in treatment-naïve subjects. However, little is known regarding its role in HIV disease course and how it influences the size of the viral reservoir once anti-retroviral therapy (ART) is started. Here, leveraging on cutting-edge bioinformatic tools, we explored the relationship between HLA class I and the HIV reservoir in a cohort of 90 people living with HIV (PLWH) undergoing ART and who achieved viral suppression. Analysis of HLA allele distribution among patients with high and low HIV reservoir allowed us to document a predominant role of HLA-B and -C genes in regulating the size of HIV reservoir. We then focused on the analysis of HIV antigen (Ag) repertoire, by investigating immunogenetic parameters such as the degree of homozygosity, HLA evolutionary distance and Ag load. In particular, we used two different bioinformatic algorithms, NetMHCpan and MixMHCpred, to predict HLA presentation of immunogenic HIV-derived peptides and identified HLA-B*57:01 and HLA-B*58:01 among the highest ranking HLAs in terms of total load, suggesting that their previously reported protective role against HIV disease progression might be linked to a more effective viral recognition and presentation to Cytotoxic T lymphocytes (CTLs). Further, we speculated that some peptide-HLA complexes, including those produced by the interaction between HLA-B*27 and the HIV Gag protein, might be particularly relevant for the efficient regulation of HIV replication and containment of the HIV reservoir. Last, we provide evidence of a possible synergistic effect between the CCR5 ∆32 mutation and Ag load in controlling HIV reservoir.

Keywords: B*27; B*57:01; B*58:01; CCR5; HIV; HLA antigens; T-cell epitopes; computational biology; immunogenetics; in silico prediction.

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References

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