Association study of common genetic variants and HIV-1 acquisition in 6,300 infected cases and 7,200 controls

Abstract

Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6 × 10⁻¹¹). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception of CCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size.

Figure 1. Association results for approximately 8 million common DNA variants tested for an impact on HIV-1 acquisition.

A) Quantile-quantile plot of association results after meta-analysis across the six groups. For each variant tested, the observed −log₁₀ p-value is plotted against the null expectation (dashed line). P-values lower than 5×10⁻⁸ are truncated for visual effect. B) Manhattan plot of association results where each variant is plotted by genomic position (x-axis) and −log₁₀ p-value (y-axis). Only variants in the MHC region on chromosome 6 have p-values below genome-wide significance (p<5×10⁻⁸ dashed line, large diamonds).

Figure 2. Common DNA variants within the MHC region that are associated with HIV-1 acquisition comparing 6,334 HIV-1 infected patients to 7,247 population controls are driven by HIV-1 controllers and not maintained when restricting to patients with known dates of seroconversion.

A) Regional association plot of the locus containing genome-wide significant SNPs after meta-analysis. The signal of association is centered on the HLA-B/HLA-C genes. The association result for the top SNP, rs4418214, is indicated by the purple diamond, with dark blue indicating SNPs in high LD (r²>0.8), light blue indicating moderate LD (r² between 0.2 and 0.8) and grey indicating low or no LD (r²<0.2) with rs4418214. The dashed line indicates genome-wide significance (p<5×10⁻⁸). The location of classical class I and class II HLA genes (green arrows) is given as reference. B) Forest plot of effect estimates for the C allele at rs4418214 with 95% confidence intervals per group (box and whiskers) and after meta-analysis (diamond). The majority of the association signal is contributed by Groups 3 and 4, which are enriched for HIV-1 controllers. C) Regional association plot of the same variants as in A) but restricting analysis to include only individuals with a known date of seroconversion to limit frailty bias.

Figure 3. Analysis of bulk SNP effects shows no evidence for enrichment of association signal across data sets.

LD pruned SNP sets falling below various p-value thresholds (grey shades, x-axis) were selected based on association results calculated in five of six groups (discovery set). Per individual scores were calculated in a non-overlapping test set (Group 3) by summing the beta-weighted dosage of all SNPs in that set. Model p-value (listed above bars) and variance explained (using Nagelkerke's pseudo R², y-axis) were calculated by regressing phenotype on per individual score using logistic regression.