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. 2015 Nov 24;112(47):14658-63.
doi: 10.1073/pnas.1514867112. Epub 2015 Nov 9.

Polymorphisms of large effect explain the majority of the host genetic contribution to variation of HIV-1 virus load

Affiliations

Polymorphisms of large effect explain the majority of the host genetic contribution to variation of HIV-1 virus load

Paul J McLaren et al. Proc Natl Acad Sci U S A. .

Abstract

Previous genome-wide association studies (GWAS) of HIV-1-infected populations have been underpowered to detect common variants with moderate impact on disease outcome and have not assessed the phenotypic variance explained by genome-wide additive effects. By combining the majority of available genome-wide genotyping data in HIV-infected populations, we tested for association between ∼8 million variants and viral load (HIV RNA copies per milliliter of plasma) in 6,315 individuals of European ancestry. The strongest signal of association was observed in the HLA class I region that was fully explained by independent effects mapping to five variable amino acid positions in the peptide binding grooves of the HLA-B and HLA-A proteins. We observed a second genome-wide significant association signal in the chemokine (C-C motif) receptor (CCR) gene cluster on chromosome 3. Conditional analysis showed that this signal could not be fully attributed to the known protective CCR5Δ32 allele and the risk P1 haplotype, suggesting further causal variants in this region. Heritability analysis demonstrated that common human genetic variation-mostly in the HLA and CCR5 regions-explains 25% of the variability in viral load. This study suggests that analyses in non-European populations and of variant classes not assessed by GWAS should be priorities for the field going forward.

Keywords: GWAS; HIV-1 control; genomics; heritability; infectious disease.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Manhattan plot of genome-wide association results. After genotype imputation, ∼8 million common variants were tested for association with spVL in 6,315 individuals of European ancestry using linear regression. Per SNP -log10(P value) (y axis) are plotted by physical position (x axis). Genome-wide signals of association (P < 5 × 10−8, dotted line) were observed on chromosomes 6 and 3. The strongest associated SNPs per region were rs59440261 on chromosome 6 (P = 2.0 × 10−83) and rs1015164 on chromosome 3 (P = 1.5 × 10−19).
Fig. 2.
Fig. 2.
Regional association plot of the chromosome 6 association peak. Association results, −log10(P value), for SNPs (gray circles), classical HLA alleles (blue boxes), and amino acids within HLA proteins (red diamonds). For biallelic markers, results were calculated by linear regression, including covariates. Association at amino acid positions with more than two alleles was calculated using a multi–degree-of-freedom omnibus test. The dashed line indicates genome-wide significance (P = 5 × 10−8). Amino acid position 97 (P = 4.6 × 10−143) in HLA-B showed the strongest association signal of any variant tested genome-wide.
Fig. 3.
Fig. 3.
Location and effect of independently associated amino acids. Three-dimensional structures of (A) HLA-B (PDB ID code 2bvp) and (B) HLA-A (PDB ID code 4hwz) proteins. Conditional analysis identified five independent amino acid positions [positions 97, 67, and 45 in HLA-B and positions 77 and 95 in HLA-A (orange residues)] that line the peptide-binding groove and explain the majority of the association signal in the MHC. (C) Effect on spVL (i.e., change in log10 HIV-1 spVL per allele copy) of individual amino acid residues at each position. Results were calculated per allele using linear regression models, including allele dosage and principal components. Gray bars indicate the estimated change in spVL per amino acid allele at each position with standard error (whiskers). All identified positions accommodate >2 amino acid alleles, with allelic effects ranging from strongly protective (i.e., viral load decreasing) to deleterious (viral load increasing). Full association statistics and amino acid allele frequencies are listed in SI Appendix, Table S4.
Fig. 4.
Fig. 4.
Regional association plot of the chromosome 3 association peak. Association results for Mb 45.5–47 (Hg19) of chromosome 3 in a subset of individuals genotyped for CCR5Δ32 (n = 5,559). P values were calculated by linear regression, including covariates. The blue diamond, red square, and red diamond indicate the association strength of the top SNP (rs4317138, P = 7.7 × 10−22), Hap-P1 (P = 1.8 × 10−19), and CCR5Δ32 (P = 1.6 × 10−16), respectively. The dashed line indicates genome-wide significance (P = 5 × 10−8).

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