Paul J. McLaren, Cedric Coulonges, István Bartha, Tobias L. Lenz, Aaron J. Deutsch, Arman Bashirova, Susan Buchbinder, Mary N. Carrington, Andrea Cossarizza, Judith Dalmau, Andrea De Luca, James J. Goedert, Deepti Gurdasani, David W. Haas, Joshua T. Herbeck, Eric O. Johnson, Gregory D. Kirk, Olivier Lambotte, Ma Luo, Simon Mallal, Daniëlle van Manen, Javier Martinez-Picado, Laurence Meyer, José M. Miro, James I. Mullins, Niels Obel, Guido Poli, Manjinder S. Sandhu, Hanneke Schuitemaker, Patrick R. Shea, Ioannis Theodorou, Bruce D. Walker, Amy C. Weintrob, Cheryl A. Winkler, Steven M. Wolinsky, Soumya Raychaudhuri, David B. Goldstein, Amalio Telenti, Paul I. W. de Bakker, Jean-François Zagury, and Jacques Fellay

PNAS 2015 112 (47) 14658-14663; GENETICS

Significance

A proportion of the variation in HIV-1 viral load in the infected population is influenced by host genetics. Using a large sample of infected individuals (n = 6,315) with genome-wide genotype data, we sought to map genomic regions that influence HIV viral load and quantify their impact. We identified amino acid positions located in the binding groove of class I HLA proteins (HLA-A and -B) and SNPs in the chemokine (C-C motif) receptor 5 gene region that together explain 14.5% of the observed variation in HIV viral load. Controlling for these signals, we estimated that an additional 5.5% can be explained by common, additive genetic variation. Thus, we demonstrate that common variants of large effect explain the majority of the host genetic component of HIV viral load.

 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.

See: http://www.pnas.org/content/112/47/14658.full

PNAS NOVEMBER 24, 2015; VOL.112, No. 47: 14658–14663

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).