Human Immunotypes Impose Selection on Viral Genotypes Through Viral Epitope Specificity

Migle Gabrielaite, Marc Bennedbæk, Adrian G Zucco, Christina Ekenberg, Daniel D Murray, Virginia L Kan, Giota Touloumi, Linos Vandekerckhove, Dan Turner, James Neaton, H Clifford Lane, Sandra Safo, Alejandro Arenas-Pinto, Mark N Polizzotto, Huldrych F Günthard, Jens D Lundgren, Rasmus L Marvig, Migle Gabrielaite, Marc Bennedbæk, Adrian G Zucco, Christina Ekenberg, Daniel D Murray, Virginia L Kan, Giota Touloumi, Linos Vandekerckhove, Dan Turner, James Neaton, H Clifford Lane, Sandra Safo, Alejandro Arenas-Pinto, Mark N Polizzotto, Huldrych F Günthard, Jens D Lundgren, Rasmus L Marvig

Abstract

Background: Understanding the genetic interplay between human hosts and infectious pathogens is crucial for how we interpret virulence factors. Here, we tested for associations between HIV and host genetics, and interactive genetic effects on viral load (VL) in HIV-positive antiretroviral treatment-naive clinical trial participants.

Methods: HIV genomes were sequenced and the encoded amino acid (AA) variants were associated with VL, human single nucleotide polymorphisms (SNPs), and imputed HLA alleles using generalized linear models with Bonferroni correction.

Results: Human (388 501 SNPs) and HIV (3010 variants) genetic data were available for 2122 persons. Four HIV variants were associated with VL (P < 1.66 × 10-5). Twelve HIV variants were associated with a range of 1-512 human SNPs (P < 4.28 × 10-11). We found 46 associations between HLA alleles and HIV variants (P < 1.29 × 10-7). HIV variants and immunotypes when analyzed separately were associated with lower VL, whereas the opposite was true when analyzed in concert. Epitope binding predictions supported our observations.

Conclusions: Our results show the importance of immunotype specificity on viral antigenic determinants, and the identified genetic interplay emphasizes that viral and human genetics should be studied in the context of each other.Clinical Trials Registration: NCT00867048.

Keywords: GWAS; HIV; genome-to-genome analysis; genome-wide association study; host genomics; viral genomics; viral load.

© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Figures

Figure 1.
Figure 1.
Schematic visualization of the 4 association analyses performed in this study. Abbreviations: AA, amino acid; HIV, human immunodeficiency virus; SNP, single nucleotide polymorphism.
Figure 2.
Figure 2.
Associations between HIV amino acid (AA) variants and HLA alleles projected on HIV genome with the strongest association for each HIV AA variant included. Red horizontal line marks the Bonferroni P value threshold (P = 1.29 × 10–7). The x-axis denotes gene AA positions. Circle size denotes the number of significantly associated host HLA alleles.
Figure 3.
Figure 3.
A, Network of the associated HLA alleles and HIV AA variants where line thickness represents the association’s strength and red arrows mark HLA alleles in LD. The opacity of the arrows corresponds to squared correlation coefficient (R2). B, Comparison between the HLA type and HIV AA associations identified in this analysis and the Bartha et al study [19]. Abbreviations: AA, amino acid; HIV, human immunodeficiency virus; LD, linkage disequilibrium; LTR, long terminal repeat.
Figure 4.
Figure 4.
Violin plots of the HIV amino acid (AA) variant and HLA alleles show the 3 associations that had a strong (P < .05) interaction effect on viral load (A–C), and the Gag242N and B*57:01 association that did not have a strong interaction effect on viral load but shows the same tendency as the Gag242N and B*57:03 association (D).

Source: PubMed

3
Se inscrever